Fall protection equipment having inductive sensor for connection status and control

ABSTRACT

Techniques are described for monitoring and controlling fall protection equipment. For example, the techniques of this disclosure may be used to monitor the connection status of fall protection equipment, e.g., whether or not the fall protection equipment is connected to a support structure. The techniques described in the disclosure may determine whether the fall protection equipment is connected to a support structure based on changes in a resonant frequency of an electronic circuit of an inductive sensor within the fall protection equipment. The inductive sensor may be formed from sets of one or more coils, where a first set of one or more coils and a second set of one or more coils are wound in opposite directions.

CROSS REFERENCE TO RELATED APPLICATIONS

This application is a national stage filing under 35 U.S.C. 371 ofPCT/US2019/016768, filed Feb. 6, 2019, which claims the benefit ofprovisional Application No. 62/628,720, filed Feb. 9, 2018, thedisclosure of which is incorporated by reference in its/their entiretyherein.

TECHNICAL FIELD

This disclosure relates to safety equipment and, in particular, fallprotection equipment.

BACKGROUND

Fall protection equipment is important safety equipment for workersoperating at potentially harmful or even deadly heights. For example, tohelp ensure safety in the event of a fall, workers often wear safetyharnesses connected to support structures with fall protection equipmentsuch as lanyards, energy absorbers, self-retracting lanyards (SRLs),descenders, and the like. When a worker is connected to a supportstructure, the worker may be referred to as being “tied off” or“anchored.” In order to maintain a safe working condition when workingat height, a worker may maintain at least one connection to a supportstructure at all times.

Fall protection equipment may include a variety of components forconnecting a worker to a support structure (also referred to as ananchorage). For example, snap hooks and carabiners may have moveablegates that allow a worker to connect to and disconnect from a supportstructure. As another example, a ladder safety sleeve may have amoveable gate that allows the worker to connect to and disconnect from aclimbing ladder fall arrest system carrier e.g., flexible cable or rigidrail support structure.

SUMMARY

In general, this disclosure describes fall protective equipment havinginductive sensors for monitoring and controlling usage of the fallprotection equipment. For example, the disclosure describes examples ofsensing techniques to confirm that a fall protection device is coupledto a support structure to ensure that a worker is properly tied off(e.g., anchored) to the structure. This disclosure describes usinginductive sensing techniques, such as detecting changes to a resonantfrequency of electronic circuits of one or more inductive sensors withinthe fall protection device, to determine whether a support structure iswithin an area of attachment of the fall protection device.

In one example, the disclosure describes a fall protection devicecomprising a body that at least partially defines an area of attachmentfor attaching the fall protection device to a support structure, amoveable gate connected to the body and configured to move between anopen position and a closed position. The open position provides accessto the area of attachment of the fall protection device and the closedposition restricts access to the area of attachment. The fall protectiondevice also includes an inductive sensor within the body for sensingwhether the support structure is within the area of attachment. Theinductive sensor includes an electrical circuit arranged within the bodyso that a resonant frequency of the electrical circuit of the inductivesensor changes when the support structure is within the area ofattachment relative to when the support structure is not within the areaof attachment.

In one example, the disclosure describes a system for fall protectiondetection, the system comprising a fall protection device comprising aninductive sensor having an electronic circuit, and one or moreprocessors coupled to the inductive sensor. The one or more processorsare configured to determine a change in a resonant frequency of theelectronic circuit of the inductive sensor, determine whether a supportstructure is within an area of attachment of the fall protection devicebased on the change in the resonant frequency of the electronic circuitof the inductive sensor, and generate information indicating whether thefall protection device is anchored to the support structure at leastbased in part on the determination of whether the support structure iswithin the area of attachment of the fall protection device.

In one example, the disclosure describes a method for fall protectiondetection, the method comprising determining a change in a resonantfrequency of an electronic circuit of an inductive sensor of a fallprotection device, determining whether a support structure is within anarea of attachment of the fall protection device based on the change inthe resonant frequency of the electronic circuit of the inductivesensor, and generating information indicating whether the fallprotection device is anchored to the support structure at least based inpart on the determination of whether the support structure is within thearea of attachment of the fall protection device.

The details of one or more examples of the disclosure are set forth inthe accompanying drawings and the description below. Other features,objects, and advantages of the disclosure will be apparent from thedescription and drawings, and from the claims.

BRIEF DESCRIPTION OF DRAWINGS

FIG. 1 is a block diagram illustrating an example system in whichpersonal protection equipment (PPEs) having embedded sensors andcommunication capabilities are utilized within a number of workenvironments and are managed by a personal protection equipmentmanagement system in accordance with various techniques of thisdisclosure.

FIG. 2 is a block diagram illustrating an operating perspective of thepersonal protection equipment management system shown in FIG. 1 .

FIG. 3 is a block diagram illustrating one example of a computing devicethat may be used to monitor and/or control fall protection equipment inaccordance with aspects of this disclosure.

FIGS. 4A and 4B are flow diagrams that together illustrate an exampleprocess for determining whether a fall protection device is anchored toa support structure.

FIG. 5 is a flow diagram illustrating an example process for determininga baseline resonant frequency of inductive sensors of a fall protectiondevice.

FIG. 6 is flow diagram illustrating an example process for determiningan average resonant frequency used for determining the baseline resonantfrequency of FIG. 5 .

FIG. 7 is a conceptual diagram illustrating an example inductive sensorof a fall protection device.

FIG. 8 is a conceptual diagram illustrating an example of a plurality ofinductive sensors of a fall protection device.

FIG. 9 is a conceptual diagram illustrating another example of aplurality of inductive sensors of a fall protection device.

FIG. 10 illustrates an example of a carabiner that is configured inaccordance with aspects of this disclosure.

FIG. 11 illustrates an example of a carrier sleeve that is configured inaccordance with aspects of this disclosure.

FIG. 12 illustrates another view of the ladder safety sleeve shown inFIG. 11 .

FIG. 13 is a conceptual diagram illustrating an example of fallprotection equipment in communication with a wearable data hub, inaccordance with various aspects of this disclosure.

FIG. 14 illustrates a state machine indicating safety status of a fallprotection device.

FIG. 15 is a flow diagram illustrating another example for determiningwhether a fall protection device is anchored to a support structure.

DETAILED DESCRIPTION

According to aspects of this disclosure, an article of fall protectiondevice may be configured to incorporate one or more inductive sensorsfor sensing operation of the fall protection device. A fall protectiondevice may generally refer to a device used to connect a user (e.g., aworker) to a support structure for the purpose of securing the user tothe support structure in the event of a fall (e.g., tying off oranchoring the worker to the support structure). Examples of fallprotection equipment include a variety of carabiners (also referred toas “spring hooks” or “snap hooks”), shackles, carrier sleeves, or otherdevices that are capable of connecting a user to and disconnecting auser from the support structure. A particular example of a snap hookthat may be adapted to incorporate certain techniques of this disclosureis the Saflok™ Snap Hook manufactured by 3M Fall Protection Business. Aparticular example of a carrier sleeve may be adapted to incorporatecertain techniques of this disclosure is the Lad-Saf™ X3 DetachableCarrier Sleeve manufactured by 3M Fall Protection Business. A supportstructure may include an anchor, a lifeline, or another structurecapable of supporting the weight of a user in the event of a fall.

In some examples, the inductive sensors senses whether a supportstructure is disposed within an area of attachment for the fallprotection equipment, or other operations or characteristics of the fallprotection equipment. For example, the electrical characteristics of theinductive sensors may be indicative of whether the worker is anchored tosupport structure. As described herein, an area of attachment of fallprotection equipment may generally refer to an area defined by one ormore components of the fall protection equipment that encompass thesupport structure. That is, when secured to a support structure, thearea of attachment is the area of the fall protection equipment in whichthe support structure is disposed. With respect to a carabiner as anexample, the area of attachment may be the interior area of thecarabiner defined by a body and a gate of the carabiner.

To be properly tied off, the fall protection device should be connectedto a support structure, typically metal, when used by a worker. Thisdisclosure describes examples of fall protection devices configured withinductive sensors that are used to determine whether a support structureis disposed within the fall protection equipment, and example algorithmsto determine whether a metal support structure is present using theexample inductive sensors.

According to aspects of this disclosure, the fall protection deviceand/or a computing device in communication with the fall protectiondevice may use information to determine electrical characteristicchanges, such as changes in resonant frequencies, in the inductivesensors arranged within the fall protection equipment to determinewhether the fall protection equipment is anchored to a metal supportstructure. As described in more detail, in response to a metal beingdisposed within the area of attached of the fall protection equipment,the resonant frequency of one or more of the inductive sensors mayshift.

For example, the electrical circuits of the inductive sensors resonateat a particular baseline resonant frequency when no metal is disposed inthe area of attachment. In particular, the inductive sensor isconfigured with a plurality of electrical coils such that when currentflows through the electrical circuits, the electrical circuits form anelectromagnetic field within the area of attachment of the fallprotection device. Accordingly, the inductive sensors may be positionedand oriented within the fall protection device so as to create theelectromagnetic field in the area of attachment when current is driventhrough their respective electrical circuits.

As such, when metal is disposed in the area of attachment, theelectromagnetic field may cause eddy currents in the metal or otherwiseinteract with the metal in a manner detectable by the inductive sensorof the fall protection device. For example, the eddy currents react withinductive sensor to form a set of coupled inductors. The coupling of theinductors in turn may change the measured resonant frequency of theelectronic circuits within the fall protection device. However, ifsomething other than metal or other conductive structure is disposed inthe area of attachment, there may not be any interaction with theelectromagnetic field, and hence no inductive coupling, and there may beno change in the measured resonant frequency of the electronic circuitsof the inductive sensors, or at least not a change more than a thresholdamount of frequency change. By detecting changes in the resonantfrequency (e.g., more than the threshold amount of frequency change suchas 5 kilo-Hertz (kHz)), the fall protection device and/or computingdevice in communication with the fall protection device may determinewhether the support structure is anchored or not anchored.

Using inductive sensors for determining whether the fall protectiondevice is anchored may provide technical advantages for various reasons.For example, conventional magnetic sensors may detect only ferrousmetal, but use of inductive sensors as described herein may provide thetechnical advantage of being capable of detecting all or almost allmetals and other conductive structures. The inductive sensors may berelatively low-power, low-cost, and durable for determining whether thestructure is proper for tying off. For example, the inductive sensorsmay not be affected in ability to determine whether the structure isproper for tying off even if the fall protection equipment is covered(e.g., with concrete or ice). However, if mechanical sensors, ratherthan inductive sensors, are covered and used in fall protection devices,there may be an impact on proper sensing of whether the fall protectiondevice is anchored. In some examples, the techniques described use acombination of mechanical sensors and inductive sensors to determinewhether the fall protection device is anchored.

Furthermore, as described in more detail, in one or more examples, theinductive sensors may be used to detect the type of metal of the supportstructure. Detecting the type of metal may be useful in variousscenarios. For example, a safety requirement may be that the fallprotection device is to anchor to steel, and not anchor to aluminum. Bydetermining the type of metal of the support structure, the exampletechniques may confirm whether fall protection device is anchored to thecorrect types of metals.

In some environments, external, distant magnetic fields (e.g., not thosecaused from current flowing through the electronic circuit) may impactthe resonant frequency of the inductive sensor, such as by affecting theinductance of the inductive sensor. These external magnetic fields maycause errors in determining whether the resonant frequency changed forthe one or more inductive sensors. In one or more examples, theinductive sensors include an inductor formed by two or more sets ofcoils (e.g., a first set of one or more coils, and a second set of oneor more coils) wound in opposite directions relative to each other. Theopposite windings of the coils cause any electric current generated inone of the coils due to the presence of external magnetic fields tosubstantially cancel any electric current generated in the other one ofthe coils due to the same external magnetic field. Because any electriccurrents caused by the external magnetic field(s) are generallycancelled out, the one or more inductive sensors may be immune orotherwise reduce the effects of the external magnetic field, therebyimproving the detection of support structures and confirmation of properanchoring of the device.

FIG. 1 is a block diagram illustrating an example computing system 2that includes a personal protection equipment management system (PPEMS)6 for managing personal protection equipment. As described herein, PPEMSallows authorized users to perform preventive occupational health andsafety actions and manage inspections and maintenance of safetyprotective equipment. By interacting with PPEMS 6, safety professionalscan, for example, manage area inspections, worker inspections, workerhealth and safety compliance training.

In general, PPEMS 6 provides data acquisition, monitoring, activitylogging, reporting, predictive analytics and alert generation. Forexample, PPEMS 6 includes an underlying analytics and safety eventprediction engine and alerting system in accordance with variousexamples described herein. As further described below, PPEMS 6 providesan integrated suite of personal safety protection equipment managementtools and implements various techniques of this disclosure. That is,PPEMS 6 provides an integrated, end-to-end system for managing personalprotection equipment, e.g., safety equipment, used by workers 8 withinone or more physical environments 10, which may be construction sites,mining or manufacturing sites or any physical environment. Thetechniques of this disclosure may be realized within various parts ofcomputing environment 2.

As shown in the example of FIG. 1 , system 2 represents a computingenvironment in which a computing device within of a plurality ofphysical environments 8A, 8B (collectively, environments 8)electronically communicate with PPEMS 6 via one or more computernetworks 4. Each of physical environment 8 represents a physicalenvironment, such as a work environment, in which one or moreindividuals, such as workers 10, utilize personal protection equipmentwhile engaging in tasks or activities within the respective environment.

In this example, environment 8A is shown as generally as having workers10, while environment 8B is shown in expanded form to provide a moredetailed example. In the example of FIG. 1 , a plurality of workers10A-10N are shown as utilizing respective fall protection devices11A-11N (collectively, fall protection devices 11), which are shown inthis example as a variety of carabiners, carrier sleeves, andself-retracting lanyards (SRLs), attached to safety support structure12.

As further described herein, each of fall protection devices 11 includesembedded inductive sensors or monitoring devices and processingelectronics configured to capture data in real-time as a user (e.g.,worker) engages in activities while wearing the fall protectionequipment. For example, as described in greater detail with respect tothe example shown in FIG. 10 , fall protection device 11 may include avariety of electronic sensors such as one or more sensors configured tosense a characteristic associated with a connection (referred to asconnection sensors) and one or more usage and environment sensors formeasuring operations of fall protection device 11. In addition, each offall protection devices 11 may include one or more output devices foroutputting data that is indicative of operation of fall protectiondevice 11 and/or generating and outputting communications to therespective worker 10. For example, fall protection devices 11 mayinclude one or more devices to generate audible feedback (e.g., one ormore speakers), visual feedback (e.g., one or more displays, lightemitting diodes (LEDs) or the like), or tactile feedback (e.g., a devicethat vibrates or provides other haptic feedback). However, such feedbackis not necessary in all examples.

In general, each of environments 8 include computing facilities (e.g., alocal area network) by which fall protection devices 11 are able tocommunicate with PPEMS 6. For examples, environments 8 may be configuredwith wireless technology, such as 802.11 wireless networks, 802.15ZigBee networks, and the like. In the example of FIG. 1 , environment 8Bincludes a local network 7 that provides a packet-based transport mediumfor communicating with PPEMS 6 via network 4. In addition, environment8B includes a plurality of wireless access points 19A, 19B that may begeographically distributed throughout the environment to provide supportfor wireless communications throughout the work environment.

Each of fall protection devices 11 is configured to communicate data,such as sensed motions, events and conditions, via wirelesscommunications, such as via 802.11 WiFi protocols, Bluetooth protocol orthe like. Fall protection devices 11 may, for example, communicatedirectly with a wireless access point 19. As another example, eachworker 10 may be equipped with a respective one of wearablecommunication hubs 14A-14M that enable and facilitate communicationbetween fall protection devices 11 and PPEMS 6. For examples, fallprotection devices 11 as well as other PPEs for the respective worker 10may communicate with a respective communication hub 14 via Bluetooth orother short range protocol, and the communication hubs may communicatewith PPEMs 6 via wireless communications processed by wireless accesspoints 19. Although shown as wearable devices, hubs 14 may beimplemented as stand-alone devices deployed within environment 8B.

In some instances, each of hubs 14 may operate as a wireless device forfall protection devices 11 relaying communications to and from fallprotection devices 11, and may be capable of buffering usage data incase communication is lost with PPEMS 6. Moreover, each of hubs 14 isprogrammable via PPEMS 6 so that local alert rules may be installed andexecuted without requiring a connection to the cloud. As such, each ofhubs 14 provides a relay of streams of usage data from fall protectiondevices 11 and/or other PPEs within the respective environment, andprovides a local computing environment for localized alerting based onstreams of events in the event communication with PPEMS 6 is lost.

As shown in the example of FIG. 1 , an environment, such as environment8B, may also be one or more wireless-enabled beacons, such as beacons17A-17C, that provide accurate location information within the workenvironment. For example, beacons 17A-17C may be GPS-enabled such that acontroller within the respective beacon may be able to preciselydetermine the position of the respective beacon. Based on wirelesscommunications with one or more of beacons 17, a given article of fallprotection devices 11 or communication hub 14 worn by a worker 10 isconfigured to determine the location of the worker within workenvironment 8B. In this way, event data reported to PPEMS 6 may bestamped with positional information to aid analysis, reporting andanalytics performed by the PPEMS.

In addition, an environment, such as environment 8B, may also be one ormore wireless-enabled sensing stations, such as sensing stations 21A,21B. Each sensing station 21 includes one or more sensors and acontroller configured to output data indicative of sensed environmentalconditions. Moreover, sensing stations 21 may be positioned withinrespective geographic regions of environment 8B or otherwise interactwith beacons 17 to determine respective positions and include suchpositional information when reporting environmental data to PPEMS 6.

As such, PPEMS 6 may be configured to correlate the sensed environmentalconditions with the particular regions and, therefore, may utilize thecaptured environmental data when processing event data received fromfall protection devices 11. For example, PPEMS 6 may utilize theenvironmental data to aid generating alerts or other instructions forfall protection devices 11 and for performing predictive analytics, suchas determining any correlations between certain environmental conditions(e.g., wind speed, heat, humidity, visibility) with abnormal workerbehavior or increased safety events. As such, PPEMS 6 may utilizecurrent environmental conditions to aid prediction and avoidance ofimminent safety events. Example environmental conditions that may besensed by sensing devices 21 include but are not limited to temperature,humidity, presence of gas, pressure, visibility, wind speed and thelike.

In example implementations, an environment, such as environment 8B, mayalso include one or more safety stations 15 distributed throughout theenvironment to provide viewing stations for accessing PPEMs 6. Safetystations 15 may allow one of workers 10 to check out one of fallprotection devices 11 and/or other safety equipment, verify that safetyequipment is appropriate for a particular one of environments 8, and/orexchange data. For example, safety stations 15 may transmit alert rules,software updates, or firmware updates to fall protection devices 11 orother equipment. Safety stations 15 may also receive data cached on fallprotection devices 11, hubs 14, and/or other safety equipment. That is,while fall protection devices 11 (and/or data hubs 14) may typicallytransmit usage data from sensors of fall protection devices 11 tonetwork 4, in some instances, fall protection devices 11 (and/or datahubs 14) may not have connectivity to network 4. In such instances, fallprotection devices 11 (and/or data hubs 14) may store usage data locallyand transmit the usage data to safety stations 15 upon being inproximity with safety stations 15. Safety stations 15 may then uploadthe data from fall protection devices 11 and connect to network 4.

In addition, each of environments 8 include computing facilities thatprovide an operating environment for end-user computing devices 16 forinteracting with PPEMS 6 via network 4. For example, each ofenvironments 8 typically includes one or more safety managersresponsible for overseeing safety compliance within the environment. Ingeneral, each user 20 interacts with computing devices 16 to accessPPEMS 6. Remote users may use computing devices 18 to interact withPPEMS via network 4. For purposes of example, the end-user computingdevices 16 may be laptops, desktop computers, mobile devices such astablets or so-called smart phones and the like.

Users 20, 24 interact with PPEMS 6 to control and actively manage manyaspects of safely equipment utilized by workers 10, such as accessingand viewing usage records, analytics and reporting. For example, users20, 24 may review usage information acquired and stored by PPEMS 6,where the usage information may include data specifying starting andending times over a time duration (e.g., a day, a week, or the like),data collected during particular events, such as detected falls, senseddata acquired from the user, environment data, and the like. Inaddition, users 20, 24 may interact with PPEMS 6 to perform assettracking and to schedule maintenance events for individual pieces ofsafety equipment, e.g., fall protection equipment 11, to ensurecompliance with any procedures or regulations. PPEMS 6 may allow users20, 24 to create and complete digital checklists with respect to themaintenance procedures and to synchronize any results of the proceduresfrom computing devices 16, 18 to PPEMS 6.

Further, in some examples, PPEMS 6 integrates an event processingplatform configured to process thousand or even millions of concurrentstreams of events from digitally enabled PPEs, such as fall protectiondevices 11. An underlying analytics engine of PPEMS 6 may applyhistorical data and models to the inbound streams to compute assertions,such as identified anomalies or predicted occurrences of safety eventsbased on conditions or behavior patterns of workers 10. PPEMS 6 mayprovide real-time alerting and reporting to notify workers 10 and/orusers 20, 24 of any predicted events, anomalies, trends, and the like.

The analytics engine of PPEMS 6 may, in some examples, apply analyticsto identify relationships or correlations between sensed worker data,environmental conditions, geographic regions and other factors andanalyze the impact on safety events. PPEMS 6 may determine, based on thedata acquired across populations of workers 10, which particularactivities, possibly within certain geographic region, lead to, or arepredicted to lead to, unusually high occurrences of safety events.

In this way, PPEMS 6 integrates comprehensive tools for managingpersonal protection equipment with an underlying analytics engine andcommunication system to provide data acquisition, monitoring, activitylogging, reporting, behavior analytics and alert generation. Moreover,PPEMS 6 provides a communication system for operation and utilization byand between the various elements of system 2. Users 20, 24 may accessPPEMS to view results on any analytics performed by PPEMS 6 on dataacquired from workers 10. In some examples, PPEMS 6 may present aweb-based interface via a web server (e.g., an HTTP server) orclient-side applications may be deployed for devices of computingdevices 16, 18 used by users 20, 24, such as desktop computers, laptopcomputers, mobile devices such as smartphones and tablets, or the like.

In some examples, PPEMS 6 may provide a database query engine fordirectly querying PPEMS 6 to view acquired safety information,compliance information and any results of the analytic engine, e.g., bythe way of dashboards, alert notifications, reports and the like. Thatis, users 24, 26, or software executing on computing devices 16, 18, maysubmit queries to PPEMS 6 and receive data corresponding to the queriesfor presentation in the form of one or more reports or dashboards. Suchdashboards may provide various insights regarding system 2, such asbaseline (“normal”) operation across worker populations, identificationsof any anomalous workers engaging in abnormal activities that maypotentially expose the worker to risks, identifications of anygeographic regions within environments 2 for which unusually anomalous(e.g., high) safety events have been or are predicted to occur,identifications of any of environments 2 exhibiting anomalousoccurrences of safety events relative to other environments, and thelike.

PPEMS 6 may simplify workflows for individuals charged with monitoringand ensure safety compliance for an entity or environment. That is, thetechniques of this disclosure may enable active safety management andallow an organization to take preventative or correction actions withrespect to certain regions within environments 8, particular articles offall protection devices 11 or individual workers 10, define and mayfurther allow the entity to implement workflow procedures that aredata-driven by an underlying analytical engine.

As one example, the underlying analytical engine of PPEMS 6 may beconfigured to compute and present customer-defined metrics for workerpopulations within a given environment 8 or across multiple environmentsfor an organization as a whole. For example, PPEMS 6 may be configuredto acquire data and provide aggregated performance metrics and predictedbehavior analytics across a worker population (e.g., across workers 10of either or both of environments 8A, 8B). Furthermore, users 20, 24 mayset benchmarks for occurrence of any safety incidences, and PPEMS 6 maytrack actual performance metrics relative to the benchmarks forindividuals or defined worker populations.

As another example, PPEMS 6 may further trigger an alert if certaincombinations of conditions are present, e.g., to accelerate examinationor service of a safety equipment, such as one of fall protection devices11. In this manner, PPEMS 6 may identify individual articles of fallprotection devices 11 or workers 10 for which the metrics do not meetthe benchmarks and prompt the users to intervene and/or performprocedures to improve the metrics relative to the benchmarks, therebyensuring compliance and actively managing safety for workers 10.

One condition that PPEMS 6, hubs 14, safety stations 15, and/orcomputing device 16 track is whether workers 10 are properly tied offwith respective fall protection devices 11 (e.g., track whether fallprotection devices 11 are anchored). For example, fall protection device11A is anchored when support structure 12 is a metal support structure,is within an area of attachment of fall protection device 11A, and agate of fall protection device 11A is closed, thereby securing fallprotection device 11A to the metal support structure. As describedherein, this disclosure describes example techniques to determinewhether fall protection devices are properly anchored based onmeasurements from sensors within respective fall protection devices 11.

As described herein, one or more of fall protection devices 11 includeone or more inductive sensors that include respective electroniccircuits having a resonant frequency based on the inductance andcapacitance of the inductive sensors. Resonant frequency, in general,describes the frequency at which a response amplitude of the electricalcircuit of the inducive sensors is at a relative maximum. In otherwords, when a signal having an input amplitude and the resonantfrequency is applied to the inductive sensor, the ratio between theoutput amplitude and the input amplitude is maximized. As described,fall protection devices 11, or other computing devices, may utilizedetection algorithms that detect changes in the resonant frequency ofthe electrical circuits of the inductive sensors if a metal structure,such as support structure 12, is proximate to the inductive sensor.

When current is driven through the electrical circuits of the inducivesensors, the inductive sensors generate an electromagnetic field withinthe area of attachment (e.g., the inductive sensors are positioned andoriented in a way to generate the electromagnetic field within the areaof attachment). The electromagnetic field may cause eddy currents togenerate within the metal structure, which in turn cause supportstructure 12 to inductively couple with the inductive sensor. Theinductive coupling causes an effective change in the overall inductance(e.g., inductance from the inductive sensor and the coupling with themetal), which in turn shifts the resonant frequency (e.g., the measuredresonant frequency).

In this disclosure, the term “baseline resonant frequency” refers to theresonant frequency of the electronic circuit of the inductive sensorwhen there is no metal structure in proximity to the inductive sensor.In one or more examples, PPEMS 6, hubs 14, safety stations 15, and/orcomputing device 16 determine whether fall protection devices 11 areanchored to a proper support structure, like support structure 12, basedon changes to the baseline resonant frequency of the one or moreinductive sensors of fall protection devices 11.

In some examples, temperature or normal prolonged use potentiallychanges the baseline resonant frequency of the inductive sensors evenwhen no metal structure is proximate to the inductive sensors. Thischange in the baseline resonant frequency may otherwise cause false orincorrect detection of anchoring. This disclosure describes exampletechniques to recalibrate for changes in the baseline resonant frequencyto ensure proper determination of anchoring. Moreover, in some workenvironments, external or stray magnetic fields may couple into theinductive sensor and cause changes in the baseline resonant frequency.This disclosure describes examples of inductive sensors that cancel outor otherwise squelch the effects of the external magnetic fields on thebaseline resonant frequency, thereby improving detection.

FIG. 2 is a block diagram providing an operating perspective of PPEMS 6when hosted as cloud-based platform capable of supporting multiple,distinct work environments 8 having an overall population of workers 10that have a variety of communication enabled personal protectionequipment (PPE), such as fall protection devices 11, respirators 13,safety helmets or other safety equipment. In the example of FIG. 2 , thecomponents of PPEMS 6 are arranged according to multiple logical layersthat implement the techniques of the disclosure. Each layer may beimplemented by one or more modules comprised of hardware, software, or acombination of hardware and software.

In FIG. 2 , personal protection equipment (PPEs) 62, such as fallprotection devices 11, respirators 13 and/or other equipment, eitherdirectly or by way of hubs 14, as well as computing devices 60, operateas clients 63 that communicate with PPEMS 6 via interface layer 64.Computing devices 60 typically execute client software applications,such as desktop applications, mobile application, and web applications.Computing devices 60 may represent any of computing devices 16, 18 ofFIG. 1 . Examples of computing devices 60 may include, but are notlimited to a portable or mobile computing device (e.g., smartphone,wearable computing device, tablet), laptop computers, desktop computers,smart television platforms, and servers, to name only a few examples.

As further described in this disclosure, PPEs 62 communicate with PPEMS6 (directly or via hubs 14) to provide streams of data acquired fromembedded sensors and other monitoring circuitry and receive from PPEMS 6alerts, configuration and other communications. Client applicationsexecuting on computing devices 60 may communicate with PPEMS 6 to sendand receive information that is retrieved, stored, generated, and/orotherwise processed by services 68. For instance, the clientapplications may request and edit safety event information includinganalytical data stored at and/or managed by PPEMS 6. In some examples,client applications 61 may request and display aggregate safety eventinformation that summarizes or otherwise aggregates numerous individualinstances of safety events and corresponding data acquired from PPEs 62and or generated by PPEMS 6. The client applications may interact withPPEMS 6 to query for analytics information about past and predictedsafety events, behavior trends of workers 10, to name only a fewexamples. In some examples, the client applications may output fordisplay information received from PPEMS 6 to visualize such informationfor users of clients 63. As further illustrated and described in below,PPEMS 6 may provide information to the client applications, which theclient applications output for display in user interfaces.

Clients applications executing on computing devices 60 may beimplemented for different platforms but include similar or the samefunctionality. For instance, a client application may be a desktopapplication compiled to run on a desktop operating system, such asMicrosoft Windows, Apple OS X, or Linux, to name only a few examples. Asanother example, a client application may be a mobile applicationcompiled to run on a mobile operating system, such as Google Android,Apple iOS, Microsoft Windows Mobile, or BlackBerry OS to name only a fewexamples. As another example, a client application may be a webapplication such as a web browser that displays web pages received fromPPEMS 6.

In the example of a web application, PPEMS 6 may receive requests fromthe web application (e.g., the web browser), process the requests, andsend one or more responses back to the web application. In this way, thecollection of web pages, the client-side processing web application, andthe server-side processing performed by PPEMS 6 collectively providesthe functionality to perform techniques of this disclosure. In this way,client applications use various services of PPEMS 6 in accordance withtechniques of this disclosure, and the applications may operate withinvarious different computing environment (e.g., embedded circuitry orprocessor of a PPE, a desktop operating system, mobile operating system,or web browser, to name only a few examples).

As shown in FIG. 2 , PPEMS 6 includes an interface layer 64 thatrepresents a set of application programming interfaces (API) or protocolinterface presented and supported by PPEMS 6. Interface layer 64initially receives messages from any of clients 63 for furtherprocessing at PPEMS 6. Interface layer 64 may therefore provide one ormore interfaces that are available to client applications executing onclients 63. In some examples, the interfaces may be applicationprogramming interfaces (APIs) that are accessible over a network.Interface layer 64 may be implemented with one or more web servers. Theone or more web servers may receive incoming requests, process and/orforward information from the requests to services 68, and provide one ormore responses, based on information received from services 68, to theclient application that initially sent the request. In some examples,the one or more web servers that implement interface layer 64 mayinclude a runtime environment to deploy program logic that provides theone or more interfaces. As further described below, each service mayprovide a group of one or more interfaces that are accessible viainterface layer 64.

In some examples, interface layer 64 may provide Representational StateTransfer (RESTful) interfaces that use HTTP methods to interact withservices and manipulate resources of PPEMS 6. In such examples, services68 may generate JavaScript Object Notation (JSON) messages thatinterface layer 64 sends back to the client application 61 thatsubmitted the initial request. In some examples, interface layer 64provides web services using Simple Object Access Protocol (SOAP) toprocess requests from client applications 61. In still other examples,interface layer 64 may use Remote Procedure Calls (RPC) to processrequests from clients 63. Upon receiving a request from a clientapplication to use one or more services 68, interface layer 64 sends theinformation to application layer 66, which includes services 68.

As shown in FIG. 2 , PPEMS 6 also includes an application layer 66 thatrepresents a collection of services for implementing much of theunderlying operations of PPEMS 6. Application layer 66 receivesinformation included in requests received from client applications 61and further processes the information according to one or more ofservices 68 invoked by the requests. Application layer 66 may beimplemented as one or more discrete software services executing on oneor more application servers, e.g., physical or virtual machines. Thatis, the application servers provide runtime environments for executionof services 68. In some examples, the functionality interface layer 64as described above and the functionality of application layer 66 may beimplemented at the same server.

Application layer 66 may include one or more separate software services68, e.g., processes that communicate, e.g., via a logical service bus 70as one example. Service bus 70 generally represents logicalinterconnections or set of interfaces that allows different services tosend messages to other services, such as by a publish/subscriptioncommunication model. For instance, each of services 68 may subscribe tospecific types of messages based on criteria set for the respectiveservice.

When a service publishes a message of a particular type on service bus70, other services that subscribe to messages of that type will receivethe message. In this way, each of services 68 may communicateinformation to one another. As another example, services 68 maycommunicate in point-to-point fashion using sockets or othercommunication mechanism. In still other examples, a pipeline systemarchitecture could be used to enforce a workflow and logical processingof data messages as they are process by the software system services.Before describing the functionality of each of services 68, the layersare briefly described herein.

Data layer 72 of PPEMS 6 represents a data repository that providespersistence for information in PPEMS 6 using one or more datarepositories 74. A data repository, generally, may be any data structureor software that stores and/or manages data. Examples of datarepositories include but are not limited to relational databases,multi-dimensional databases, maps, and hash tables, to name only a fewexamples. Data layer 72 may be implemented using Relational DatabaseManagement System (RDBMS) software to manage information in datarepositories 74. The RDBMS software may manage one or more datarepositories 74, which may be accessed using Structured Query Language(SQL). Information in the one or more databases may be stored,retrieved, and modified using the RDBMS software. In some examples, datalayer 72 may be implemented using an Object Database Management System(ODBMS), Online Analytical Processing (OLAP) database or other suitabledata management system.

As shown in FIG. 2 , each of services 68A-68H (“services 68”) isimplemented in a modular form within PPEMS 6. Although shown as separatemodules for each service, in some examples the functionality of two ormore services may be combined into a single module or component. Each ofservices 68 may be implemented in software, hardware, or a combinationof hardware and software. Moreover, services 68 may be implemented asstandalone devices, separate virtual machines or containers, processes,threads or software instructions generally for execution on one or morephysical processors.

In some examples, one or more of services 68 may each provide one ormore interfaces that are exposed through interface layer 64.Accordingly, client applications of computing devices 60 may call one ormore interfaces of one or more of services 68 to perform techniques ofthis disclosure.

In some examples, services 68 may include an event processing platformincluding an event endpoint frontend 68A, event selector 68B, eventprocessor 68C and high priority (HP) event processor 68D. Event endpointfrontend 68A operates as a front-end interface for receiving and sendingcommunications to PPEs 62 and hubs 14. In other words, event endpointfrontend 68A operates to as a front-line interface to safety equipmentdeployed within environments 8 and utilized by workers 10.

In some instances, event endpoint frontend 68A may be implemented as aplurality of tasks or jobs spawned to receive individual inboundcommunications of event streams 69 from the PPEs 62 carrying data sensedand captured by the safety equipment. When receiving event streams 69,for example, event endpoint frontend 68A may spawn tasks to quicklyenqueue an inbound communication, referred to as an event, and close thecommunication session, thereby providing high-speed processing andscalability. Each incoming communication may, for example, carry datarecently captured data representing sensed conditions, motions,temperatures, actions or other data, generally referred to as events.Communications exchanged between the event endpoint frontend 68A and thePPEs may be real-time or pseudo real-time depending on communicationdelays and continuity.

Event selector 68B operates on the stream of events 69 received fromPPEs 62 and/or hubs 14 via frontend 68A and determines, based on rulesor classifications, priorities associated with the incoming events.Based on the priorities, event selector 68B enqueues the events forsubsequent processing by event processor 68C or high priority (HP) eventprocessor 68D. Additional computational resources and objects may bededicated to HP event processor 68D so as to ensure responsiveness tocritical events, such as incorrect usage of PPEs, use of incorrectfilters and/or respirators based on geographic locations and conditions,failure to properly secure fall protection equipment 11 and the like.Responsive to processing high priority events, HP event processor 68Dmay immediately invoke notification service 68E to generate alerts,instructions, warnings or other similar messages to be output to fallprotection devices 11, hubs 14 and/or remote users 20, 24. Events notclassified as high priority are consumed and processed by eventprocessor 68C.

In general, event processor 68C or high priority (HP) event processor68D operate on the incoming streams of events to update event data 74Awithin data repositories 74. In general, event data 74A may include allor a subset of usage data obtained from PPEs 62. For example, in someinstances, event data 74A may include entire streams of samples of dataobtained from electronic sensors of PPEs 62. In other instances, eventdata 74A may include a subset of such data, e.g., associated with aparticular time period or activity of PPEs 62.

Event processors 68C, 68D may create, read, update, and delete eventinformation stored in event data 74A. Event information for may bestored in a respective database record as a structure that includesname/value pairs of information, such as data tables specified inrow/column format. For instance, a name (e.g., column) may be “workerID” and a value may be an employee identification number. An eventrecord may include information such as, but not limited to: workeridentification, PPE identification, acquisition timestamp(s) and dataindicative of one or more sensed parameters.

In addition, event selector 68B directs the incoming stream of events tostream analytics service 68F, which represents an example of ananalytics engine configured to perform in depth processing of theincoming stream of events to perform real-time analytics. Streamanalytics service 68F may, for example, be configured to process andcompare multiple streams of event data 74A with historical data andmodels 74B in real-time as event data 74A is received. In this way,stream analytic service 68D may be configured to detect anomalies,transform incoming event data values, trigger alerts upon detectingsafety concerns based on conditions or worker behaviors.

Historical data and models 74B may include, for example, specifiedsafety rules, business rules and the like. In this way, historical dataand models 74B may characterize activity of a user of fall protectiondevices 11, e.g., as conforming to the safety rules, business rules, andthe like. In addition, stream analytic service 68D may generate outputfor communicating to PPEs 62 by notification service 68F or computingdevices 60 by way of record management and reporting service 68G.

Analytics service 68F may process inbound streams of events, potentiallyhundreds or thousands of streams of events, from enabled safety PPEs 62utilized by workers 10 within environments 8 to apply historical dataand models 74B to compute assertions, such as identified anomalies orpredicted occurrences of imminent safety events based on conditions orbehavior patterns of the workers. Analytics service 68D may publish theassertions to notification service 68F and/or record management byservice bus 70 for output to any of clients 63.

In this way, analytics service 68F may configured as an active safetymanagement system that predicts imminent safety concerns and providesreal-time alerting and reporting. In addition, analytics service 68F maybe a decision support system that provides techniques for processinginbound streams of event data to generate assertions in the form ofstatistics, conclusions, and/or recommendations on an aggregate orindividualized worker and/or PPE basis for enterprises, safety officersand other remote users. For instance, analytics service 68F may applyhistorical data and models 74B to determine, for a particular worker,the likelihood that a safety event is imminent for the worker based ondetected behavior or activity patterns, environmental conditions andgeographic locations.

In some examples, analytics service 68F may generate user interfacesbased on processing information stored by PPEMS 6 to provide actionableinformation to any of clients 63. For example, analytics service 68F maygenerate dashboards, alert notifications, reports and the like foroutput at any of clients 63. Such information may provide variousinsights regarding baseline (“normal”) operation across workerpopulations, identifications of any anomalous workers engaging inabnormal activities that may potentially expose the worker to risks,identifications of any geographic regions within environments for whichunusually anomalous (e.g., high) safety events have been or arepredicted to occur, identifications of any of environments exhibitinganomalous occurrences of safety events relative to other environments,and the like.

Although other technologies can be used, in one example implementation,analytics service 68F utilizes machine learning when operating onstreams of safety events so as to perform real-time analytics. That is,analytics service 68F includes executable code generated by applicationof machine learning to training data of event streams and known safetyevents to detect patterns. The executable code may take the form ofsoftware instructions or rule sets and is generally referred to as amodel that can subsequently be applied to event streams 69 for detectingsimilar patterns and predicting upcoming events.

Analytics service 68F may, in some example, generate separate models fora particular worker, a particular population of workers, a particularenvironment, or combinations thereof. Analytics service 68F may updatethe models based on usage data received from PPEs 62. For example,analytics service 68F may update the models for a particular worker, aparticular population of workers, a particular environment, orcombinations thereof based on data received from PPEs 62.

Alternatively, or in addition, analytics service 68F may communicate allor portions of the generated code and/or the machine learning models tohubs 14 (or PPEs 62) for execution thereon so as to provide localalerting in near-real time to PPEs. Example machine learning techniquesthat may be employed to generate models 74B can include various learningstyles, such as supervised learning, unsupervised learning, andsemi-supervised learning. Example types of algorithms include Bayesianalgorithms, Clustering algorithms, decision-tree algorithms,regularization algorithms, regression algorithms, instance-basedalgorithms, artificial neural network algorithms, deep learningalgorithms, dimensionality reduction algorithms and the like. Variousexamples of specific algorithms include Bayesian Linear Regression,Boosted Decision Tree Regression, and Neural Network Regression, BackPropagation Neural Networks, the Apriori algorithm, K-Means Clustering,k-Nearest Neighbour (kNN), Learning Vector Quantization (LUQ),Self-Organizing Map (SOM), Locally Weighted Learning (LWL), RidgeRegression, Least Absolute Shrinkage and Selection Operator (LASSO),Elastic Net, and Least-Angle Regression (LARS), Principal ComponentAnalysis (PCA) and Principal Component Regression (PCR).

Record management and reporting service 68G processes and responds tomessages and queries received from computing devices 60 via interfacelayer 64. For example, record management and reporting service 68G mayreceive requests from client computing devices for event data related toindividual workers, populations or sample sets of workers, geographicregions of environments 8 or environments 8 as a whole, individual orgroups/types of PPEs 62. In response, record management and reportingservice 68G accesses event information based on the request. Uponretrieving the event data, record management and reporting service 68Gconstructs an output response to the client application that initiallyrequested the information.

As additional examples, record management and reporting service 68G mayreceive requests to find, analyze, and correlate PPE event information.For instance, record management and reporting service 68G may receive aquery request from a client application for event data 74A over ahistorical time frame, such as a user can view PPE event informationover a period of time and/or a computing device can analyze the PPEevent information over the period of time.

In example implementations, services 68 may also include securityservice 68H that authenticate and authorize users and requests withPPEMS 6. Specifically, security service 68H may receive authenticationrequests from client applications and/or other services 68 to accessdata in data layer 72 and/or perform processing in application layer 66.An authentication request may include credentials, such as a usernameand password. Security service 68H may query security data 74A todetermine whether the username and password combination is valid.Configuration data 74D may include security data in the form ofauthorization credentials, policies, and any other information forcontrolling access to PPEMS 6. As described above, security data 74A mayinclude authorization credentials, such as combinations of validusernames and passwords for authorized users of PPEMS 6. Othercredentials may include device identifiers or device profiles that areallowed to access PPEMS 6.

Security service 68H may provide audit and logging functionality foroperations performed at PPEMS 6. For instance, security service 68H maylog operations performed by services 68 and/or data accessed by services68 in data layer 72. Security service 68H may store audit informationsuch as logged operations, accessed data, and rule processing results inaudit data 74C. In some examples, security service 68H may generateevents in response to one or more rules being satisfied. Securityservice 68H may store data indicating the events in audit data 74C.

PPEMS 6 may include self-check component 68I, self-check criteria 74Eand work relation data 74F. Self-check criteria 74E may include one ormore self-check criterion. Work relation data 74F may include mappingsbetween data that corresponds to PPE, workers, and work environments.Work relation data 74F may be any suitable datastore for storing,retrieving, updating and deleting data. Work relation data store 74F maystore a mapping between the unique identifier of worker 10A and a uniquedevice identifier of data hub 14A. Work relation data store 74F may alsomap a worker to an environment. In the example of FIG. 2 , self-checkcomponent 68I may receive or otherwise determine data from work relationdata 74F for data hub 14A, worker 10A, and/or PPE associated with orassigned to worker 10A. Based on this data, self-check component 68I mayselect one or more self-check criteria from self-check criteria 74E.Self-check component 68I may send the self-check criteria to data hub14A.

In some examples, event processor 68C and record management andreporting service 68G may generate information indicative of whetherfall protection devices 11 are properly anchored. For example, fallprotection devices 11 may be configured to transmit information that isultimately received by PPEMS 6 that indicates whether fall protectiondevices 11 are anchored based on whether a resonant frequency ofinductive sensors of fall protection devices 11 changed. Event processor68C may process the data indicating whether fall protection devices 11are anchored, and reporting services 68G generate reports indicatingwhether fall protection devices 11 are anchored. For instance, reportingservices 68G may generate reports indicating how long, how often, when,etc. each one of fall protection devices 11 were anchored, where suchinformation is generated based on sensing by inductive sensors of fallprotection devices 11 including information of whether a resonantfrequency of electronic circuits of the inductive sensors changed. Insome examples, event processor 68B and notification service 68E maytogether generate alerts if workers 10 are not compliant with properanchoring of fall protection devices 11.

FIG. 3 illustrates an example of a computing device that may beincorporated in an article of fall protection devices 11. For ease, theexample is illustrated with respect to fall protection device 11A. Fallprotection devices 11B-11N may be substantially similar, includingidentical, to fall protection device 11A.

In the illustrated example, computing device 98 includes processors 100,inductive sensing processor 101, memory 102, communication unit 104, oneor more connection sensors 106, fall protection unit 108, one or moreusage and environment sensors 110, and output unit 112. It should beunderstood that the architecture and arrangement of computing device 98illustrated in FIG. 3 is shown for exemplary purposes only. In otherexamples, computing device 98 incorporated in an article of fallprotection device 11A may be configured in a variety of other wayshaving additional, fewer, or alternative components than those shown inFIG. 3 . For example, as described in greater detail below, computingdevice 98 may be configured to include only a subset of components, suchas communication unit 104 and connection sensors 106 and may offloadcertain processing functions to anther device, such as one of hubs 14.

As one example, computing device 98 includes inductive sensing processor101 that determines a resonant frequency of inductive sensors of sensors106. In some examples, processors 100 further process informationindicative of the resonant frequency. In some examples, communicationunit 104 outputs information indicative of the resonant frequency forprocessing by other processors such as those of hubs 14 or PPEMS 6, astwo non-limiting examples. For ease, the examples are described withrespect to processors 100, but should be understood that the operationsof processors 100 may be performed by other processors such as those ofhubs 14 or PPEMS 6, or by a combination of processors 100 and otherprocessors.

In general, computing device 98 include a plurality of sensors thatcapture real-time data regarding operation of fall protection device 11Aand/or an environment in which fall protection device 11A is used. Suchdata is referred to herein as usage data. Processors 100, in oneexample, are configured to implement functionality and/or processinstructions for execution within computing device 98. For example,processors 100 may be capable of processing instructions stored bymemory 102. Processors 100 may include, for example, microprocessors,digital signal processors (DSPs), application specific integratedcircuits (ASICs), field-programmable gate array (FPGAs), or equivalentdiscrete or integrated logic circuitry. Furthermore, in some examplesprocessors 100 may be analog components such as adders, comparators,low-pass filters, and like. In this disclosure, the operations ofprocessors 100 may be performed by DSPs, ASICs, FPGA, or byfixed-function analog circuitry like filters, comparators, and adders.

Memory 102 may include a computer-readable storage medium orcomputer-readable storage device. In some examples, memory 102 mayinclude one or more of a short-term memory or a long-term memory. Memory102 may include, for example, random access memories (RAM), dynamicrandom access memories (DRAM), static random access memories (SRAM),magnetic hard discs, optical discs, flash memories, or forms ofelectrically programmable memories (EPROM) or electrically erasable andprogrammable memories (EEPROM).

In some examples, memory 102 may store an operating system (not shown)or other application that controls the operation of components ofcomputing device 98. For example, the operating system may facilitatethe communication of data from electronic sensors (e.g., connectionsensors 106) to communication unit 104. In some examples, memory 102 isused to store program instructions for execution by processors 100.Memory 102 may also be configured to store information within computingdevice 98 during operation.

Computing device 98 may use communication unit 104 to communicate withexternal devices via one or more wired or wireless connections.Communication unit 104 may include various mixers, filters, amplifiersand other components designed for signal modulation, as well as one ormore antennas and/or other components designed for transmitting andreceiving data. Communication unit 104 may send and receive data toother computing devices using any one or more suitable datacommunication techniques. Examples of such communication techniquesinclude TCP/IP, Ethernet, Wi-Fi, Bluetooth, 4G, LTE, to name only a fewexamples. In some instances, communication unit 104 operates inaccordance with the Bluetooth Low Energy (BLU) protocol.

Connection sensors 106 include a wide variety of sensors incorporated infall protection device 11A and configured to generate output dataindicative of an operation of fall protection device 11A or acharacteristic of fall protection device 11A. For example, theconnection sensors 106 may capture data that is indicative of a relativeposition of a component of fall protection device 11A or senseelectrical characteristics (e.g., resonant frequency) indicative ofwhether a support structure is within an area of attachment for fallprotection device 11A. Example connection sensors 106 include one ormore switches, hall effect sensors, magnetic sensors, optical sensors,ultrasonic sensors, photoelectric sensors, rotary encoders,accelerometers, or the like. Particular examples of connection sensors106 are described with respect to the examples of FIGS. 7-9 below.

As described in more detail, connection sensors 106 include one or moreinductive sensors used to determine whether fall protection device 11Aproperly anchored to support structure 12. To be properly anchored, somebusiness or safety requirements may dictate that fall protection device11A should be anchored to a metal structure (e.g., support structure 12should be metal structure). In one or more examples, the electricalcharacteristics of the one or more inductive sensors may indicatewhether a metal support structure 12 is within fall protection device11A.

The inductive sensors are tuned for a certain resonant frequency,referred to as baseline resonant frequency. The baseline resonantfrequency is the resonant frequency of an inductive sensor when theinductive sensor is not inductively coupled with metal structureexternal to the fall protection device 11A. When the inductive sensorsare proximate to metal, such as when metal is disposed within the areaof attachment of fall protection device 11A, the resonant frequency ofthe inductive sensors may change. Processors 100, in some examples, areconfigured to determine whether there is a change in the resonantfrequency of one or more inductive sensors of connection sensors 106from the baseline resonant frequency. Based on whether there is a changein the resonant frequency, processors 100 or some other processordetermines whether fall protection device 11A is anchored to supportstructure 12.

As illustrated, computing device 98 includes inductive sensing processor101. Inductive sensing processor 101 may be part of processors 100, butis illustrated separately to ease with understanding. Inductive sensingprocessor 101 determines respective resonant frequencies of theinductive sensors of connection sensors 106. One example of inductivesensing processor 101 is the LDC1612/14 Multi-Channel 28-Bit Inductanceto Digital Converter (LDC) for Inductive Sensing chip from TexasInstruments®. The output of inductive sensing processor 101 may be adigital signal indicating the resonant frequency of the inductivesensor(s) coupled to inductive sensing processor 101. Processors 100receive the digital signal indicating the resonant frequency, anddetermine whether a support structure is within the area of attachmentof fall protection device 11A based on whether there is a change in theresonant frequency.

In some examples, memory 102 stores baseline resonant frequency valuesof the inductive sensors of connection sensors 106. As described in moredetail, the baseline resonant frequency values may change due totemperature and aging of the inductive sensors, and therefore,processors 100 may update the baseline resonant frequency values andstore new baseline resonant frequency values in memory 102. For eachinductive sensor, processors 100 determine difference values, where eachdifference value is indicative of a difference between the measuredresonant frequency, measured by inductive sensing processor 101, and itscurrent baseline resonant frequency value.

Processors 100 utilize the difference values for each of the inductivesensors to determine whether there is sufficient change in the resonantfrequency to determine that metal is within the area of attachment offall protection device 11A. As one example, if any of the differencevalues are greater than a frequency change threshold value, thenprocessors 100 may determine that metal is disposed in the area ofattachment of fall protection device 11A. However, due to the locationsof the inductive sensors and the location of metal within the area ofattachment, there is a possibility that metal is within the area ofattachment but none of the difference values are greater than thefrequency change threshold value. To address such a possibility, in someexamples, processors 100 sum one or more of the difference values, andcompare the summed difference value to the frequency change thresholdvalue. Processors 100 may determine that metal is disposed within fallprotection device 11A if summed difference value is greater than thefrequency change threshold value.

In some examples, to further ensure that metal is disposed within fallprotection device 11A, processors 100 may determine difference valuesbetween previous resonant frequencies (e.g., measured resonantfrequencies of the inductive sensors that were previously measured) andthe current baseline resonant frequency values. Processors 100 may useboth sets of difference values (e.g., difference values between measuredresonant frequencies and current baseline resonant frequency values anddifference values between previous resonant frequencies and currentbaseline resonant frequency values) to determine whether metal isdisposed within the area of attachment of fall protection device 11A.

In the above example, processors 100 used the current baseline resonantfrequency. Again, baseline resonant frequency is the resonant frequencyof an inductive sensor when no metal is disposed within the area ofattachment. Due to changes in the temperature, wear-and-tear, etc., thebaseline resonant frequency may change for the inductive sensors. Thisdisclosure, further below, describes examples for determining thecurrent baseline resonant frequency.

Processors 100 may generate information indicating whether the fallprotection device 11A is anchored to the support structure at leastbased in part on the determination of whether the support structure iswithin the area of attachment. For example, if determined that a metalsupport structure is within the area of attachment, processors 100 maygenerate a signal indicating as such. Communication unit 104 and/oroutput unit 112 may then output the information to hubs 14 or some otherdevice that decide whether worker 10A is safely secured to the supportstructure. In some examples, processors 100 may be configured todetermine whether worker 10A is safely secured to the support structurewithout needing to output the generated signal indicating that the metalsupport structure is within the area of attachment.

In some examples, communication unit 104 and/or output unit 112 mayoutput information indicating whether fall protection device 11A isanchored to another one of fall protection devices 11. As an example, ina system of two or more fall protection devices 11, one (e.g., fallprotection device 11A) serves as a bridge between the other fallprotection devices 11 and all external computing devices (e.g., hub 14,PPEMS 6). This is done wirelessly. In some examples, fall protectiondevices 11 may already communicate with each other to maintain asynchronized state table, so each one of fall protection devices 11 isfully aware of the state of the other fall protection devices 11. Assuch, the external computing device may communicate with only one offall protection devices 11 to determine the complete states of all fallprotection devices 11.

Fall protection unit 108 may include any combination of hardware andsoftware (e.g., executable by processors 100) to control the operationof a lock 109 (as described in greater detail, for example, with respectto FIGS. 10-12 below) incorporated in fall protection device 11A. Asdescribed herein, a lock may include any device capable of impeding orpreventing fall protection device 11A from being disconnected from asupport structure. As merely one example and as described in greaterdetail with respect to the example shown in FIG. 12 , lock 109 mayinclude a solenoid that extends to prevent the movement of one or morecomponents of fall protection device 11A to impede or prevent fallprotection device from being disconnected from a support structure. Asanother lock 109 keeps a movable gate of fall protection device 11Aclosed. Fall protection unit 108 may be configured to control theoperation of lock 109 and/or feedback component 113, e.g., based on datafrom connection sensors 106.

Usage and environment sensors 110 may include a wide variety of sensorsthat capture data indicative of manner in which of fall protectiondevice 11A is being used or an environment in which fall protectiondevice 11A is disposed. For example, usage and environment sensors 110may include accelerometers, location sensors, altimeters, or the like.In this example, an accelerometer may be configured to generate dataindicative of an acceleration of fall protection device 11A with respectto gravity. An accelerometer may be configured as a single- ormulti-axis accelerometer to determine a magnitude and direction ofacceleration, e.g., as a vector quantity, and may be used to determineorientation, coordinate acceleration, vibration, shock, and/or falling.A location sensor may be configured to generate data indicative of alocation of fall protection device 11A in one of environments 8. Thelocation sensor may include a Global Positioning System (GPS) receiver,componentry to perform triangulation (e.g., using beacons and/or otherfixed communication points), or other sensors to determine the relativelocation of fall protection device 11A. An altimeter may be configuredto generate data indicative of an altitude of fall protection device 11Aabove a fixed level. In some examples, the altimeter may be configuredto determine altitude of fall protection device 11A based on ameasurement of atmospheric pressure (e.g., the greater the altitude, thelower the pressure). In addition, status and environment sensors 110 mayinclude one or more sensors configured to measure wind speed,temperature, humidity, particulate content, noise levels, air quality,or any variety of other characteristics of environments in which fallprotection device 11A may be used.

Output unit 112 may be configured to output data that is indicative ofoperation of fall protection device 11A, e.g., as measured by one ormore sensors of computing device 98. In some examples, output unit 112may directly output the data from the sensors of computing device 98.For example, output unit 112 may generate one or more messagescontaining real-time or near real-time data from one or more sensors ofcomputing device 98 for transmission to another device via communicationunit 104. However, in some instances, communication unit 104 may not beable to communicate with such devices, e.g., due to an environment inwhich fall protection device 11A is located and/or network outages. Insuch instances, output unit 112 may cache usage data to memory 102. Thatis, output unit 112 (or the sensors themselves) may store usage data tomemory 102, which may allow the usage data to be uploaded to anotherdevice upon a network connection becoming available.

Output unit 112 may also be configured to generate an audible, visual,tactile, or other output that is perceptible by a user of fallprotection device 11A. For example, output unit 112 may include one moreuser interface devices including, as examples, a variety of lights,displays, haptic feedback generators, speakers or the like. In oneexample, output unit 112 may include one or more light emitting diodes(LEDs) that are located on fall protection device 11A and/or included ina remote device that is in a field of view of a user of fall protectiondevice 11A (e.g., indicator glasses, visor, or the like). In anotherexample, output unit 112 may include one or more speakers that arelocated on fall protection device 11A and/or included in a remote device(e.g., earpiece, headset, or the like). In still another example, outputunit 112 may include a haptic feedback generator that generates avibration or other tactile feedback and that is included on fallprotection device 11A or a remote device (e.g., a bracelet, a helmet, anearpiece, or the like). In still another example, output unit 112 maygenerate an electronic message for transmission to another computingdevice, such as end-user computing devices 16, computing devices 18,safety stations 15, hubs 14 (FIG. 1 ) or any other computing device.

As described above, processors 100 generate information indicatingwhether fall protection device 11A is anchored. In some examples,processors 100 may cause output unit 112 to output information to worker10A indicating whether he/she is properly anchored based on theinformation indicating whether fall protection device 11A is anchored.

In operation, fall protection unit 108 (or another computing devicecapable of communicating with computing device 98) may use data fromconnection sensors 106 to determine whether fall protection device 11Ais connected to a support structure. For example, fall protection unit108 may receive data from connections sensors 106 that indicates astatus or an operation of components of fall protection device 11A. Fallprotection unit 108 may determine a connection status of a plurality ofarticles of fall protection device 11A based on the received data. Forexample, fall protection unit 108 may determine that a particulararticle of fall protection device 11A is connected to a supportstructure based on data indicating that components of fall protectiondevice 11A have been moved to allow connection to the support structureand that the support structure is disposed within an area of attachmentof fall protection device 11A.

In some instances, fall protection unit 108 may control the operation oflock 109 and/or feedback component 113 based on the determinedconnection status. For example, based on determining that fallprotection device 11A of fall protection devices 11 is the only fallprotection device that is connected to the support structure (e.g.,according to the determined connection status), fall protection unit 108may actuate lock 109 in order to impede or prevent fall protectiondevice 11A from being disconnected from the support structure.

In some examples, lock 109 may be a secondary or tertiary lock of fallprotection device 11A. For example, certain safety standards or codesmay require at least two separate and deliberate actions for componentsof fall protection device 11A to move (e.g., for a gate to move),thereby allowing fall protection device 11A to connect to or disconnectfrom a support structure. As described in greater detail below withrespect to FIGS. 10 and 11 , each separate and deliberate action may beassociated with a locking mechanism. According to aspects of thisdisclosure, lock 109 may prevent one or more of such locking mechanismsfrom being operated, e.g., from being opened to allow disconnection fromthe support structure.

Fall protection unit 108 may also release lock 109. For example, afteractuating lock 109, fall protection unit 108 may continue to monitorwhether fall protection device 11A is connected to the supportstructure. In the event that one or more other articles of fallprotection device 11A are connected to the support structure, fallprotection unit 108 may release lock 109 such that lock 109 no longerimpedes fall protection device 11A from being disconnected from thesupport structure.

In the event that fall protection unit 108 actuates lock 109, outputunit 112 may generate a signal that indicates lock 109 has beenactuated. For example, as described above, output unit 112 may generatean audible, visual, and/or tactile output that indicates lock 109 hasbeen actuated. In some examples, output unit 112 may additionally oralternatively generate an electronic message that indicates lock 109 hasbeen actuated for transmission to another computing device, such asend-user computing devices 16, computing devices 18, safety stations 15,hubs 14 (FIG. 1 ) or any other computing device.

In some instances, lock 109 may incorporate a manual override. Forexample, a user may manually perform one or more actions to release lock109 from a locked position to an unlocked position. In addition to orinstead of the alerts described above, output unit 112 may generate asignal that indicates lock 109 has been manually overridden by a user offall protection device 11A. For example, output unit 112 may generate anelectronic message, an audible output, a visual output, and/or tactileoutput that indicates a manual override has been performed.

In some examples, rather than actuating lock 109 (or in addition toactuating lock 109), fall protection unit 108 may actuate feedbackcomponent 113 based on the determined connection status. For example,based on determining that a particular article of fall protection device11A is the only fall protection device that is connected to the supportstructure (e.g., according to the determined connection status), fallprotection unit 108 may generate alert data and transmit the alert datato feedback component 113. Upon receiving the alert data, fallprotection device 11A may generate an alert that indicates that the fallprotection device 11A is the only article of fall protection device thatis connected to the at least one support structure. That is, in someexamples, feedback component 113 may generate an audible alert (e.g.,via one or more speakers), a visual alert (e.g., via one or moredisplays, light emitting diodes (LEDs) or the like), or a tactile alert(e.g., via a component of fall protection device 11A that vibrates orprovides other haptic feedback). In other examples, as noted above,output unit 112 may generate an electronic message that indicates theconnection status, e.g., for transmission to another device such ascomputing devices 18 (FIG. 1 ). In some examples, according to aspectsof this disclosure, fall protection unit 108 may determine whether afall has occurred. For example, fall protection unit 108 may receivedata from connection sensors 106 that indicates a load being applied tofall protection device 11A. In response to the load exceeding apredetermined threshold, fall protection unit 108 may generate anaudible, visual or tactile alert for output by output unit 112. In someexamples, fall protection unit 108 may also determine a duration withwhich the load is applied, e.g., to determine not only that a user hasfallen (thereby generating the load), but is also suspended post fall.

FIGS. 4A and 4B are flow diagrams that together illustrate an exampleprocess for determining whether a fall protection device is anchored toa metal structure. As described above, computing device 98 includesinductive sensing processor 101 configured to determine a resonantfrequency of the inductive sensors of connection sensors 106. If theresonant frequency of an inductive sensor changes, the change may beindicative that there is a metal structure within an area of attachmentof fall protection device 11A. If there is a metal structure within thearea of attachment, in some examples, processors 100 may be configuredto generate information indicating that fall protection device 11A isproperly tied off (e.g., properly anchored). In some examples,processors 100 uses information indicating that the resonant frequencychanged, and that the moveable gate of fall protection device 11A isclosed to determine that fall protection device 11A is properlyanchored.

For ease, the examples of FIGS. 4A and 4B are described with respect toprocessors 100. However, in some examples, processors 100 collectsinformation indicative of the resonant frequencies and outputs suchinformation to hubs 14, safety stations 15, computing device 16, and/orPPEMS 6, and one or more of hubs 14, safety stations 15, computingdevice 16, and/or PPEMS 6 determine whether fall protection device 11Ais properly anchored. Accordingly, the example techniques described withrespect to processors 100 may be performed by processors 100, one ormore of hubs 14, safety stations 15, computing device 16, and/or PPEMS6, or a combination thereof.

The examples of FIGS. 4A and 4B are described with respect to therebeing two inductive sensors in sensors 106. However, there may be onlyone inductive sensor in sensors 106 or three or more inductive sensors.The example techniques may operate in a substantially similar manner,except if there is only one inductive sensor, some of the summingoperations described below are not be necessary.

In the examples of FIGS. 4A and 4B, the operations for the first andsecond inductive sensors are illustrated as occurring in parallel withone other. However, the examples of FIGS. 4A and 4B should not beconsidered so limited. The example operations for the first and secondinductive sensors may occur substantially at the same time, overlappingin time, or sequentially. Also, example operations, described above,that utilize previously stored values, such as in memory 102, mayretrieve the values and perform operations on the values in parallel,overlapping in time, or sequentially.

As illustrated, inductive sensing processor 101 determines a currentresonant frequency for a first inductive sensor (120A), and determines acurrent resonant frequency for a second inductive sensor (120B). In oneor more example, inducive sensing processor 101 is configured toperiodically determine the resonant frequency of each of the inductivesensors (e.g., every 100-200 milliseconds (ms)). In some examples,inductive sensing processor 101 determines the resonant frequency ofeach of the inductive sensors more often if the moveable gate is closed,as compared to if the moveable gate is opened, thereby conserving powerby not determining the resonant frequency as often when the gate isopen.

One example way to determine the resonant frequency is for inductivesensing processor 101 to output a pulse having an input amplitude atdifferent frequencies and measure the output amplitude for each of thefrequencies. Inductive sensing processor 101 may determine a ratiobetween the output amplitude and the input amplitude for each of thefrequencies of the pulse. The frequency at which the ratio of the outputamplitude to the input amplitude is the greatest may be indicative ofthe resonant frequency, and inductive sensing processor 101 outputsinformation indicating the resonant frequency to processors 100 forfurther processing.

In FIG. 4A, processors 100 determine a current estimate of baselineresonant frequency for the first inductive sensor (122A), and a currentestimate of baseline resonant frequency for the second inductive sensor(122B). Examples of techniques for determining the current estimate ofbaseline resonant frequencies are described in more detail with respectto FIGS. 5 and 6 .

The baseline resonant frequency of an inductive sensor is the resonantfrequency of the inductive sensor when there is no metal in proximity tothe inductive sensor. Each of the inductive sensor is tuned for aparticular resonant frequency (e.g., 4.5 MHz), and an initial estimateof the baseline resonant frequency may be the resonant frequency forwhich the inductive sensor was tuned. However, due to aging and otherfactors, the baseline resonant frequency may change. Accordingly, insome examples, processors 100 periodically determine the baselineresonant frequency of the inductive sensors.

Processors 100 use the baseline resonant frequencies to determinewhether the current resonant frequencies are different than the baselineresonant frequencies. For example, processors 100 determine a differencebetween current resonant frequency and estimate of baseline resonantfrequency for the first inductive sensor (124A). In this manner,processors 100 determine a first difference value indicating a change ina resonant frequency of the first inductive sensor. Processors 100determine a difference between current resonant frequency and estimateof baseline resonant frequency for the second inductive sensor (124B).In this manner, processors 100 determine a second difference valueindicating a change in a resonant frequency of the second inductivesensor.

In determining the difference, processors 100 subtract the estimate ofthe baseline resonant frequency, represented as “u”, from the currentresonant frequency, represented as “f,” as measured by the inductivesensing processor. In other words, processors 100 determine (f-u) forthe first inducive sensor and determine (f-u) for the second inductivesensor. The order of the operations (e.g., u is subtracted from f) maybe useful in certain situations. For example, if metal is disposedwithin the area of attachment, at the resonant frequencies for which theinductive sensors are designed (e.g., approximately 4.5 MHz), theresonant frequency should increase. Therefore, if metal is disposedwithin the area of attachment, then (f-u) should be a positive number.

As another example, assume that the baseline resonant frequency is 100kHz or lower. In such examples, if steel or iron is within the area ofattachment, the resonant frequency should increase. If aluminum iswithin the area of attachment, the resonant frequency should decrease.Therefore, if (f-u) is a positive number, then processors 100 maydetermine that steel or iron is within the area of attachment, but if(f-u) is a negative number, the processor 100 may determine thataluminum is within the area of attachment. Whether the resonantfrequency shifts upwards or downwards may be a factor of thepermeability, the metal type, and resonant frequency. For a highresonant frequency (e.g., 1 MHz or greater), the permeability may notaffect the resonant frequency. But for low resonant frequency (e.g., 100kHz or lower), the permeability may affect the resonant frequency. Insome examples, at lower baseline resonant frequencies, iron or steelcause the resonant frequency to shift upwards, but aluminum causes theresonant frequency to shift downwards, and the direction of shift isused to determine the type of metal within the area of attachment.

As noted above, the inductive sensors are configured for a resonantfrequency of approximately 1 MHz or greater such as 4.5 MHz. One reasonfor selecting such a high resonant frequency is that inductive couplingfrom metal (e.g., metal commonly suitable as support structures for fallprotection devices 11) may only cause the resonant frequency toincrease. If the resonant frequency were selected at a lower frequency,the inductive coupling from the metal may cause the resonant frequencyto increase or decrease due to the permeability of the metal. Forexample, if the resonant frequency for which the inducive sensors areconfigured is too low, then it may be possible that eddy currents causethe resonant frequency to increase, but the coupling due to thepermeability of the metal causes the resonant frequency to decrease,resulting in no or little overall change in the resonant frequency. Inthis case, although metal is disposed within the area of attachment,there may not be change in the resonant frequency, and processors 100may incorrectly determine that there is no metal within the area ofattachment. By selecting a sufficiently high resonant frequency for theinductive sensors, the effects of the permeability may be negated, andthe resonant frequency consistently increases when metal is disposedwithin the area of attachment.

In some examples, the permeability of the metal may be used as anadvantage to determine the type of metal within the area of attachment.For instance, if the baseline resonant frequency is set to be relativelylow (e.g., 100 kHz), processors 100 may determine the direction of shift(e.g., upwards or downwards relative to the baseline resonant frequency)to determine the type of metal.

In the example illustrated in FIG. 4A, processors 100 sum thedifferences (e.g., sum the first difference value and the seconddifference value) to generate a first summed change in resonantfrequency value (126). In examples where there is only one inductivesensor, processors 100 may not perform such summing, and in suchexamples, the first summed change in resonant frequency value is equalto the first difference value. In examples where there are three or moreinductive sensors, processors 100 may sum the difference values for allof the inductive sensors to generate a first summed change in resonantfrequency value.

In some examples, processors 100 rely on the first summed change inresonant frequency value to determine whether a metal structure isdisposed within an area of attachment of fall protection device 11A toensure that proper anchoring. For example, processors 100 determinewhether the first summed change in resonant frequency is greater than afrequency change threshold value (e.g., 5 kHz). If the first summedchange in resonant frequency is greater than the frequency changethreshold value, processors 100 determine that metal is disposed withinthe area of attachment, and if the gate is closed, generate informationindicating that that fall protection device 11A is anchored. If thefirst summed change in resonant frequency is less than or equal to thefrequency change threshold value, processors 100 determine that metal isnot disposed within the area of attachment, and generate informationindicating that fall protection device 11A is not anchored or tied off.

The frequency change threshold value may be based on the baselineresonant frequency. For example, an electronic circuit having a baselineresonant frequency of 4.5 MHz may need a frequency change threshold of 5kHz to detect particular metal support structure and rejectenvironmental noise. However, an electronic circuit having a baselineresonant frequency of 8 MHz may need a frequency change threshold of 10kHz for detection and rejection of environmental noise.

However, to further ensure accuracy in the determination of whether fallprotection device 11A is anchored, processors 100 may rely on previousresonant frequency measurements of the first and second inductivesensors. Inductive sensing processor 101 stores the measured resonantfrequency values in memory 102. In some examples, processors 100determine a previous resonant frequency for the first inductive sensor(128A), and a previous resonant frequency for the second inductivesensor (128B). As one example, the previous resonant frequency for thefirst and second inductive sensors may be the immediately precedingmeasured resonant frequencies (e.g., the resonant frequency valuesmeasured immediately before the current measured resonant frequencies).

Processors 100 determine a difference between the previous resonantfrequency of the first inductive sensor and the current estimate ofbaseline resonant frequency for the first inductive sensor (130A). Inthis example, the previous resonant frequency is the value thatprocessors 100 retrieved from memory 102 that was previously determinedby inductive sensing processor 101 as the resonant frequency for thefirst inductive sensor, but the baseline resonant frequency is thecurrent estimate of the baseline resonant frequency, and not a previousestimate. Processors 100 determine a difference between the previousresonant frequency of the second inductive sensor and the currentestimate of baseline resonant frequency for the second inductive sensor(130B). In this example, the previous resonant frequency is the valuethat processors 100 retrieved from memory 102 that was previouslydetermined by inductive sensing processor 101 as the resonant frequencyfor the second inductive sensor, but the baseline resonant frequency isthe current estimate of the baseline resonant frequency, and not aprevious estimate.

In the example illustrated in FIG. 4A, processors 100 sum thedifferences to generate a second summed change in resonant frequencyvalue (132). Referring to FIG. 4B, processors 100 compare the first andsecond summed change in resonant frequency values to the frequencychange threshold value (134), and determine whether a metal supportstructure is within the area of attachment of fall protection device 11Abased on the comparison.

For example, processors 100 determine whether both the first and secondsummed change in resonant frequency values are less than the frequencychange threshold value (136). If both the first and second summed changein resonant frequency values are less than the frequency changethreshold value (YES of 136), then processors 100 may determine thatfall protection device 11A is unanchored and generate informationindicating that fall protection device 11A is unanchored. In someexamples, processors 100 may determine that fall protection device 11Ais anchored, even if both the first and second summed change in resonantfrequency values are less than the frequency change threshold value. Forinstance, as described below, if processors 100 had previouslydetermined that fall protection device 11A was anchored, and since then,processors 100 have not determined that the gate opened, then processors100 may determine that fall protection device 11A is anchored even ifboth the first and second summed change in resonant frequency values areless than the frequency change threshold value.

If processors 100 determine that both the first and second summed changein resonant frequency values are not less than the frequency changethreshold value (NO of 136), then one or may be both of first and secondsummed change in resonant frequency values is greater than the frequencychange threshold value. Processors 100 may determine whether both thefirst and second summed change in resonant frequency values are greaterthan or equal to the frequency change threshold value (140).

If both the first and second summed change in resonant frequency valuesare greater than or equal to the frequency change threshold value (YESof 140), processors 100 may determine that fall protection device 11A isanchored (142). Processors 100 may generate information indicating thatfall protection device 11A is anchored. In some examples, processors 100may only determine that the area of attachment surrounds a supportstructure when both the first and second summed change in resonantfrequency values are greater than or equal to the frequency changethreshold value. In such examples, processors 100 may not determine thatfall protection device 11A is anchored unless two conditions are met:(1) both the first and second summed change in resonant frequency valuesare greater than or equal to the frequency change threshold value, and(2) that the moveable gate is closed (e.g., a gate of fall protectiondevice 11A is in a closed position).

If both the first and second summed change in resonant frequency valuesare not greater than or equal to the frequency change threshold value(NO of 140), processors 100 may determine that there is no change in thestatus of fall protection device 11A (144). If processors 100 hadpreviously determined that fall protection device 11A was anchored, thenprocessors 100 may keep the status of fall protection device 11A asanchored, and if processors 100 had previously determined that fallprotection device 11A was unanchored, then processors 100 may keep thestatus of fall protection device 11A as unanchored.

In some examples, summing difference values of the differences betweencurrent resonant frequency and estimate of baseline resonant frequencymay be optional. For instance, processors 100 may determine whether thedifference values for any of the inductive sensors is greater than thefrequency change threshold value, and only if the difference values forany of the inductive sensors is greater than the frequency changethreshold value do processors 100 determine that fall protection device11A is anchored (or at least that, an area of attachment of fallprotection device 11A surrounds a support structure). Again, adifference value here refers to a subtraction of the current estimate ofthe baseline resonant frequency for an inductive sensor from its currentresonant frequency.

However, summing the difference values, as described above with respectto FIG. 4A, may be beneficial. In some examples, due to the location ofthe support structure within the area of attachment, the supportstructure may partially couple with one of the inductive sensors, andpartially couple with other inductive sensors. For example, due to thelocation of the support structure within the area of attachment, thesupport structure may couple with the first inductive sensor in such away to increase its resonant frequency by 2 kHz, and couple with thesecond inductive sensor in such a way to increase its resonant frequencyby 4 kHz. If the frequency change threshold value was 5 kHz, then, inthis case, processors 100 may not determine that a support structure iswithin the area of attachment if processors 100 compare each differencevalue to the threshold because 2 kHz and 4 kHz are both less than 5 kHz.If the sum is used, then processors 100 may correctly determine that asupport structure is within the area of attachment because 6 kHz (2kHz+4 kHz) is greater than 5 kHz.

Also, relying upon both the first summed change in resonant frequencyand the second summed change in resonant frequency for determine whetherfall protection device 11A is anchored or unanchored may be beneficial.In some examples, the inductive sensing processor may determine theresonant frequencies every 100 ms to 500 ms. If two consecutivemeasurements of the resonant frequencies indicate that fall protectiondevice 11A is anchored or unanchored, then there is high likelihood thatfall protection device 11A is truly anchored or unanchored. If, however,two consecutive measurements of the resonant frequencies do not indicatethat fall protection device 11A is anchored or unanchored, then it ispossible that one of the two measurement is incorrect, and for safety,processors 100 may not change the status of fall protection device 11A.

In some examples, baseline resonant frequency measurements may be notneeded, and the example techniques may be performed based on rate ofchanges in the resonant frequencies of the electronic circuits of theinductive sensors. For example, processors 100 or inductive sensingprocessor 101 store measured resonant frequency values in memory 102.Processors 100 may determine the change in frequency of the measuredfrequency values over time (e.g., frequency gradient). Because theresonant frequency should increase when the electronic circuit is inpresence of a support structure, a high-slope positive frequencygradient may mean that fall protection device 11A moved close to thesupport structure. Likewise, a high-slope negative frequency gradientmay mean that fall protection device 11A moved away from a supportstructure.

In this case, the threshold may be on the frequency gradient rather thanon a particular absolute frequency (e.g., change in X Hz/sec rather than5 kHz). The gradient threshold may be chosen to be high enough to beunlikely to be caused by natural frequency drift or environmental noise,perhaps something like 100 kHz/s. Furthermore, the gradient thresholdsmay be different for identifying the state transitions. As one example,a first threshold of +80 kHz/s may be for identifying arrival at ananchor (e.g., a support structure is arriving within fall protectiondevice 11A) and −50 kHz/s for identifying departure from an anchor(e.g., a support structure is leaving from fall protection device 11A).

In the examples illustrated in FIGS. 4A and 4B, processors 100 and/orinductive sensing processor 101 determine a change in a resonantfrequency of the electronic circuit of an inductive sensor, anddetermine whether a support structure is within an area of attachmentbased on the change in the resonant frequency. In the examplesillustrated in FIGS. 4A and 4B, the change in the resonant frequency isa change measured in difference of Hertz, and based on whether thedifference is sufficient, processors 100 may generate informationindicating whether the fall protection device 11A is anchored to thesupport structure.

In the example illustrated in FIG. 15 , processors 100 and/or inductivesensing processor 101 may determine a change in a resonant frequency ofthe electronic circuit of the inductive sensor. However, processors 100and/or inductive sensing processor 101 may determine a rate of change ina resonant frequency of the electronic circuit of the inductive sensor(400). For example, processors 100 may determine how fast the resonantfrequency changed, and whether the resonant frequency increase (e.g.,positive slope), or decreased (e.g., negative slope). In this example, achange in the resonant frequency refers to the rate of change of theresonant frequency.

In FIG. 15 , to determine whether a support structure is within an areaof attachment based on the change in the resonant frequency, processors100 may determine whether the support structure is within the area ofattachment of fall protection device 11A based on the rate of change inthe resonant frequency (410). For example, if the rate of change ispositive and greater than first threshold, then processors 100 maydetermine that the support structure is within the area of attachment.If the rate of change is negative and the absolute value is greater thana second threshold, then processors 100 may determine that the supportstructure is not within the area of attachment. The first and secondthreshold values may be difference.

Similar to above, processors 100 may generate information indicatingwhether fall protection device 11A is anchored (420). For example, fallprotection device 11A may generate audible, visual, or haptic feedback,the other types of information described to indicate whether fallprotection device 11A is anchored, or other types of feedback.

FIG. 5 is a flow diagram illustrating an example process for determininga baseline resonant frequency of inductive sensors of a fall protectiondevice. In the example, of FIGS. 4A and 4B, processors 100 determinedthe estimate of the baseline resonant frequency. FIG. 5 illustratesexamples of techniques for determining the current estimate of thebaseline resonant frequency. The example of FIG. 5 is described withrespect to one inductive sensor, but the example techniques areapplicable to the other inductive sensors as well.

As described above, inducive sensing processor 101 periodicallydetermines the resonant frequencies of the inductive sensors. Theoperations illustrated in FIG. 5 may start in response to inducivesensing processor 101 determining the resonant frequencies.

For example, processors 100 determine whether fall protection device 11Awas previously determined as being anchored (e.g., based on the resultsof the operations of FIGS. 4A and 4B) (146). Initially, such as untilprocessors 100 have made a determination that fall protection device 11Ais anchored, processors 100 may be configured to determine that fallprotection device 11A is unanchored. However, even if assumed that fallprotection device 11A is unanchored, but fall protection device 11A isactually anchored, as described in more detail, the example techniquesmay correct for this incorrect initial state.

If processors 100 had previously determined that fall protection device11A is anchored (YES of 146), then processors 100 do not update theestimate to the baseline resonant frequency (148). For instance, ifdetermined that fall protection device 11A was previously determined tobe anchored, then a metal support structure is within the area ofattachment. As described above, the baseline resonant frequency is thefrequency of an inductive sensor when the metal support structure is notwithin the area of attachment. Hence, if the metal support structure iswithin the area of attachment, a measurement of the resonant frequencywould not be a measurement of a baseline resonant frequency.

If processors 100 had previously determined that fall protection device11A is not anchored (NO of 146), then the inductive sensing processordetermines the current baseline resonant frequency of an inducive sensor(150). If fall protection device 11A was previously determined to not beanchored, then metal structure may not be within the area of attachment,and the measurement may be an actual measurement of the baselineresonant frequency.

In some examples, processors 100 set the measured baseline resonantfrequency as the estimated baseline resonant frequency. However, thereis variability in how much the baseline resonant frequency changes fromone measurement to another, or there may be errors in the measurement.Accordingly, processors 100 may apply a smoothing algorithm so that theestimate of the baseline resonant frequency does not shift drasticallyand lessens the effect from erroneous measurements.

For example, processors 100 read current average resonant frequency ofthe inductive sensor (152). The current average resonant frequency isindicative of a running average of baseline resonant frequency valuesthat processors 100 utilize to control the amount by which processors100 adjust the measured baseline resonant frequency. Memory 102 may beconfigured to store values of the measured baseline resonantfrequencies. For example, when the inductive sensing processordetermines a resonant frequency, the inductive sensing processor maystore a value indicative of the resonant frequency in memory 102. Foreach of the resonant frequency values, processors 100 may indicatewhether the value corresponds to a baseline resonant frequency or not.For example, when determined that fall protection device 11A is notanchored (e.g., NO of 146), for resonant frequency measurements taken bythe inductive sensing processor, processors 100 may identify theseresonant frequency measurements as baseline resonant frequency values.When determined that fall protection device 11A is anchored (e.g., YESof 146), for resonant frequency measurements taken by the inductivesensing processor, processors 100 may identify these resonant frequencymeasurements as not being baseline resonant frequency values.

In some examples, processors 100 determine the current average resonantfrequency based on the actual measured baseline resonant frequencies,and not based on any smoothing that may have been performed. Examples oftechniques to determine the current average resonant frequency isdescribed in more detail with respect to FIG. 6 .

Processors 100 determine a difference between the current resonantfrequency of the inductive sensor and the current average resonantfrequency of the inductive sensor (154). Processors 100 determine thecurrent estimate of the baseline resonant frequency based on thedifference. For example, processors 100 may adjust a value indicatingthe current resonant frequency towards the current average resonantfrequency of the inductive sensor based on the difference to determinean adjusted value. Processors 100 set the current estimate of thebaseline resonant frequency equal to the adjusted value (158). Thisestimate of the baseline resonant frequency is what processors 100 usewhen performing the example operations of FIGS. 4A and 4B.

As an example, processors 100 adjust the measured baseline resonantfrequency towards the current average resonant frequency in arate-limited fashion (e.g., add or subtract only a portion of thedifference, such as 5%). For example, if the difference between thecurrent average resonant frequency and the measured baseline resonantfrequency is “X,” and the current average resonant frequency is greaterthan the measured baseline resonant frequency, then processors 100 add0.05*X to the measured baseline resonant frequency value. Processors 100set the value for the estimate of the baseline resonant frequency equalto (measured baseline resonant frequency+0/05*X). By slowly increasingthe estimate of the baseline resonant frequency, the stability of theoverall system may be improved. For example, slow adaptation (e.g.,slowly increasing the estimate of the baseline resonant frequency) maybe analogous to low-pass filter, reducing the effects of transientenvironmental noise.

FIG. 6 is flow diagram illustrating an example process for determiningan average resonant frequency used for determining the baseline resonantfrequency of FIG. 5 . Processors 100 may determine whether there aresufficient data points (e.g., sufficient number of baseline resonantfrequency measurements from the inductive sensing processor stored inmemory 102) (160). The set of data points is referred to as a window ofresonant frequency measurements. As one example, the number of datapoints (e.g., size of the window) is five. If there are not sufficientnumber of baseline resonant frequency measurements (NO of 160),processors 100 may not update the value of the current average resonantfrequency (162).

If there are sufficient number of baseline resonant frequencymeasurements (YES of 160), processors 100 retrieve the baseline resonantfrequency measurements from memory 102 (164). Processors 100 determinean average of the retrieved baseline resonant frequency measurements(174). Examples of the average as used in this disclosure refers to themean, median, or mode, and includes examples where any weighting isapplied to the values. Averaging refers to any technique to performoperations on a set of numbers to output a single number, and examplesof such operations are mean, mode, and median.

In some examples, rather than performing an average on the retrievedbaseline resonant frequency measurements, processors 100 may determinewhether there are any errors in the baseline resonant frequencymeasurements and whether the errors are less than a threshold number oferrors (170). An error in a baseline resonant frequency measurement maybe where the baseline resonant frequency value is greater than or lessthan a maximum or minimum value. An error in a baseline resonantfrequency measurement may be where the baseline resonant frequency valuedeviates from the other baseline resonant frequency values by more thana deviation threshold. Other example ways to determine if there areerror values in the baseline resonant frequency measurement arepossible.

If there are not less than a threshold number of errors (NO of 170),processors 100 may not update the value of the current average resonantfrequency (162). If there are less than or equal to a threshold numberof errors (YES of 170), processors 100 remove the error values from theretrieved baseline resonant frequency measurements (172), and determinethe average by using remaining baseline resonant frequency measurements(174). In some examples, processors 100 substitute values for theerroneous baseline resonant frequency measures. For example, processors100 determine the average by using additional baseline resonantfrequency measurements from memory 102 and the remaining baselineresonant frequency measurements. In some examples, processors 100interpolate additional values from the remaining baseline resonantfrequency measurements, and determine the average by using theinterpolated values and the remaining baseline resonant frequencymeasurements. Other ways in which to substitute values for the erroneousvalues are possible.

In some examples, processors 100 set the determined average value as thecurrent average resonant frequency. However, in some examples,processors 100 determines whether to set the determine average value asthe current average resonant value based on whether there is sufficientdifference between the determined average resonant frequency and apervious average of the resonant frequency of a window of resonantfrequency measurements.

For example, processors 100 determine a difference value indicative of adifference in the determined average resonant frequency and a previousaverage of the resonant frequency, and determine whether the differenceis less than or equal to an average frequency change threshold value(176). If the difference value is less than or equal to the averagefrequency change threshold value (YES of 176), then processors 100 set avalue of the current average resonant frequency equal to the currentaverage value (178). If the difference value is not less than or equalto the average frequency change threshold value (NO of 176), thenprocessors 100 set a value of the current average resonant frequencyequal to a weighted average of the current average value and theprevious average value (180). For example, processors 100 may determinea fraction of the difference (e.g., 50% of the difference) between thedetermined average resonant frequency value and the previous average ofthe resonant frequency. Processors 100 add the fractional value to thedetermined average resonant frequency value if the previous average ofthe resonant frequency is greater than the determined average resonantfrequency, and set the resulting value as a value of the current averageresonant frequency. Processors 100 subtracts the fractional value fromthe determined average resonant frequency value if the previous averageof the resonant frequency is less than the determined average resonantfrequency, and set the resulting value as a value of the current averageresonant frequency.

FIG. 7 is a conceptual diagram illustrating an example inductive sensorof a fall protection device. FIG. 7 illustrates inductive sensor 182,that as one example includes an electronic circuit having capacitors C1and C2 and an inductor formed with coils 184A and 184B. In FIG. 7 , theinductor is formed by coils 184A and 184B coupled together via a jumperor through printed circuit board (PCB) 188 on which coils 184A and 184Bare formed. One example of PCB 188 is a thin sheet (e.g., 0.35 mmthick±10%) of FR4 material, and in some examples, the sheet for FR4material is flexible to be bend around a bowl of fall protection device11A. The bowl of fall protection device 11A partially surrounds (e.g.,may not completely enclose) the area of attachment of fall protectiondevice 11A. The area of attachment of fall protection device 11A and thebowl of fall protection device 11A are illustrated and described in moredetail in FIG. 10 .

In the example of FIG. 7 , coils 184A and 184B form a general shape oflemniscate (e.g., figure “8”). Coils 184A and 184B include one or moreturns, and in the example of FIG. 7 , coils 184A and 184B each includefour turns. A turn is one loop through coils 184A or 184B.

Coil 184A terminates at node N1, and coil 184B terminates at node N2.Nodes N1 and N2 may be coupled via a jumper connection to form a singleinductor. In some examples, coil 184A is formed on a first side of PCB188, and coil 184B is formed on a second, opposite side of PCB 188. Insuch examples, N1 and N2 may be coupled with plated vias that are formedthrough PCB 188 to form a single inductor. In one example, theinductance of the inductor formed by coils 184A and 184B isapproximately 1 micro-Henry (uH) and formed with approximately (e.g.,±10%) 9 mm wide copper with a total length of approximately (e.g., ±10%)50 mm. The size and inductance of the inductor is provided as oneexample, and should not be considered limiting. In general, the size ofthe inductor may be a function of the size and shape of fall protectiondevice 11A, as well as available space within fall protection device 11Aand the flexibility of PCB 188. Accordingly, the size of the inductor,and hence its inductance, are a matter of design choice and may bedifferent than the examples described in this disclosure.

The electronic circuit of inductive sensor 182 also includes one or morecapacitors connected in a parallel with the inductor forming a so-called“LC resonant circuit.” As illustrated, the electronic circuit ofinductive sensor 182 includes capacitors C1 and C2 connected in parallelwith the inductor. A resonant frequency of the LC resonant circuit ofinductive sensor 182 is based on the inductance of the inductor and thecapacitance of C1 and C2. The equation for the resonant frequency of theLC resonant circuit is 1/(2*pi*sqrt(L*C)), where pi is approximately3.1415, sqrt( ) is the square-root operation, L is the inductance, and Cis the total capacitance.

In one example, the baseline resonant frequency of the LC resonantcircuit of inductive sensor 182 is approximately 4.5 MHz. Again, thebaseline resonant frequency refers to the resonant frequency of theelectronic circuit when a metal support structure is not proximate tothe electronic circuit. If the inductance is 1 uH, then the totalcapacitance from C1 and C2 is 1240 pico-Farad (pF) to achieve 4.5 MHz.For example, C1 is approximately 1000 pF, and C2 is approximately 240pF. As another example, if the inductance is 3.25 uH and the totalcapacitance is 390 pF, then the baseline resonant frequency isapproximately 4.5 MHz.

Although two capacitors are shown, in some examples, there may be onlyone capacitor, and in some examples, there may be more than twocapacitors coupled in parallel. The number of capacitors may be afunction of the size and shape of the capacitors, as well as theflexibility of PCB 188. If the desired resonant frequency is differentthan 4.5 MHz, then the inductance and capacitance may be adjustedaccordingly to achieve the desired resonant frequency.

When a support structure is within an area of attachment of fallprotection device 11A, the resonant frequency of the electronic circuit(e.g., LC resonant circuit) of inductive sensor 182 shifts. As oneexample, when a metal anchor is within the area of attachment of fallprotection device 11A, the resonant frequency of the electronic circuitshifts up due to eddy currents produced in the support structure. Forexample, the eddy currents in the support structure cause the effectiveinductance of the inductor to reduce, and a reduction in the effectiveinductance causes the resonant frequency of the electronic circuit toshift up. In one example, if the support structure is proximate to theelectronic circuit, the resonant frequency shifts up by approximately 5kHz or more. As described above, the shift in the resonant frequency maybe indicative of whether the support structure is within the area ofattachment of fall protection device 11A. Also, the amount by which theresonant frequency shifts may be a function of the baseline resonantfrequency.

In some examples, the support structure may also affect the totalcapacitance of the electronic circuit of inductive sensor 182. Forexample, each turn of coils 184A and 184B creates capacitance withincoils 184A and 184B. A metal support structure proximate to inductivesensor 182 may increase the capacitance between the turns of coils 184Aand 184B, which also contributes to the shift the resonant frequency ofthe electronic circuit of inductive sensor 182.

Whether the resonant frequency of the electronic circuit of inductivesensor 182 shifts upwards (i.e., adds too) or downwards (i.e., subtractsfrom) relative to the baseline resonant frequency (e.g., resonantfrequency of the electronic circuit when no metal is proximate to theelectronic circuit) is based on the baseline resonant frequency and thetype of metal. For example, the conductance and permeability of themetal affect whether the resonant frequency shifts up or down. Theamplitude of eddy currents may be based on the conductance of the metal,and the higher the amplitude of eddy currents, the more the effectiveinductance of the electronic circuit is decrease, leading to an increasein the resonant frequency. However, the permeability of the metal maycause the effective inductance to increase, thereby causing a decreasein the resonant frequency.

At high resonant frequencies, such as 4.5 MHz or greater, the effects ofthe permeability of the metal are minimized. Accordingly, in the examplewhere the baseline resonant frequency of the electronic circuit isapproximately is 4.5 MHz, there may not be affects from the permeabilityof the support structure, and the resonant frequency may shift onlyupwards in response to a support structure being proximate to inductivesensor 182.

In some examples, forming the electronic circuit to have a lowerbaseline resonant frequency may be useful for determining the type ofmetal. As one example, the baseline resonant frequency of the electroniccircuit is less than 100 kHz, which is below the typical fall-off inpermeability of steel. In such examples, if the support structure is asteel support structure and is proximate to inductive sensor 182, theresonant frequency of the electronic circuit may shift downward from thebaseline resonant frequency of 100 kHz. However, if the supportstructure is an aluminum support structure and is proximate to inductivesensor 182, the resonant frequency of the electronic circuity may shiftupward from the baseline resonant frequency of 100 kHz. Accordingly,based on whether the resonant frequency shifted upwards or downwards,processors 100 may determine the type of metal (e.g., whether thesupport structure is steel or aluminum).

The lemiscate form of coils 184A and 184B may provide immunity toexternal magnetic fields that may perturb operation of inductive sensor182. For example, in FIG. 7 , coils 184A and 184B are wound in oppositedirections relative to one another. Accordingly, a distant magneticfield (e.g., one not produced by inductive sensor 182) may coupleapproximately equally into each of coils 184A and 184B. Since coils 184Aand 184B are wound in opposite directions relative to one another, thesignal produced by the external magnetic field in coils 184A tends tocancel the signal produced in coils 184B.

For example, FIG. 7 illustrates current path 186 through coils 184A and184B, where current path 186 is an example of how a current flowsthrough inductive sensor 182. The flow of current may be part ofdetermining the resonant frequency of the electronic circuit ofinductive sensor 182. As illustrated, current path 186 starts from theleft-side of the inductor, through the top of coils 184A, and then thecurrent through current path 186 flows counter-clockwise through coils184B until reaching node N2. Current path 186 proceeds from node N2 tonode N1, and the current through current path 186 flows clockwisethrough coils 18A, and then exits at the bottom of the left-side of theinductor. In this example, because the current flows clockwise throughcoils 184A and counter-clockwise through coils 184B, coils 184A and 184Bmay be considered as being wound in opposite directions relative to oneanother.

The current flowing through current path 186 causes an electromagneticfield to form in the area of attachment of fall protection device 11A.Eddy currents then form in a metal support structure responsive to themetal structure being in the area of attachment. The eddy currents thencause coupling with the inductor and lower the effective overallinductance. Accordingly, inductive sensor 182 may be positioned andoriented in a such a manner to cause the electromagnetic field to begenerated within the area of attachment.

Although the examples are described with coils 184A and 184B forming ageneral shape of a lemiscate, the techniques described in thisdisclosure are not so limited. In some examples, rather than using coils184A and 184B, the inductor of the electronic circuit of inductivesensor 182 may be formed with one coil. In some examples, the inductorof the electronic circuit of inductive sensor 182 may be formed withmore than two sets of coils (e.g., more than coils 184A and 184B). Also,the form need not necessarily be of a lemiscate. For example, coils 184Aand 184B may be formed as ovals that are not arranged in a way so as toform a figure “8.”

In FIG. 7 , each of the turns of coils 184A and 184B are illustrated asbeing formed on the surface of PCB 188. In some examples, coils 184A and184B may be arranged in three-dimensional space such that coils 184A and184B extend vertically out from PCB 188. Moreover, as described above,although coils 184A and 184B are shown as being on the same side of PCB188, the example techniques are not so limited. For example, coils 184Amay be on a first side of PCB 188, and coils 184B may be on a secondside of PCB 188. By having coils 184A and 184B on different sides, eachof coils 184A and 184B may include more turns and thus a higherinductance relative to the example where coils 184A and 184B are on thesame side. A higher inductance results in a higher quality (Q) factor ofthe electronic circuit (all else being equal) and higher effectiveparallel resistance. Having higher Q factor and higher effectiveparallel resistance may be beneficial because some integrated circuitsthat are used for inductive sensing have a minimum parallel resistancerequirement, and also having a higher Q gives a sharper resonant peak,resulting in more accurate detection of the resonant frequency.

The parallel resistance (Rp) is the impedance of the circuit atresonance and is a purely real number (complex component=0). In an idealcase, it is infinite, but due to energy losses in real inductors andcapacitors, it is a finite value. For example, a real parallel LCcircuit (e.g., the electronic circuit illustrated in FIG. 7 ) will havesome loss (such as losses in the dielectric of the capacitor and lossesin the series resistance of the inductor, and may be losses that occuras the magnetic field of the inductor couples into other lossymaterials) which can be modeled as a resistance in parallel with anideal (i.e., lossless) LC circuit. At resonance, the reactance of the Land C cancel one another, leaving only the parallel resistance, Rp. Theloss mechanisms are still in play at resonance, (still modeled as Rp)because current is still flowing in the reactive components, where thelosses originate.

A high Rp is desirable because, as with Ohmic losses in DC circuits, ahigh Rp will produce a higher voltage across the circuit for a givencurrent through the circuit. The Rp is also related to the Q of thecircuit. A high Q is desirable because it implies high Rp and alsobecause the resonance is more “peaky” and thus easier to identify. Forexample, inductive sensing processor 101 may more accurately determinethe resonant frequency, because with a high Q, the top of the peakshowing the resonant frequency is higher than a relatively flat peak.

As described above, inductive sensor 182 is located within fallprotection device 11A (e.g., within a bowl of fall protection device11A). In some cases, the metal material (e.g., carbon steel or aluminum)of fall protection device 11A may affect the inductance of inductivesensor 182 similar to how the support structure affects the inductance(e.g., by producing eddy currents). Accordingly, it is possible for themetal material of fall protection device 11A to cause a shift in theresonant frequency, and cause processors 100 to determine that a supportstructure is within the area of attachment. For example, without theshielding material, the resonant frequency (assuming 4.5 MHz baselineresonant frequency) may shift by 110 kHz due to the metal within fallprotection device 11A.

In some examples, fall protection device 11A includes shieldingmaterial, such as ferrite material, but other material may be used, thatis placed to surround (e.g., flank) inductive sensor 182 andelectrically decouple inductive sensor 182 from the metal within fallprotection device 11A. For example, the shielding material blocks themagnetic field generated by current flowing through inductive sensor 182from inducing eddy currents in the metal of fall protection device 11A.

The thickness of the shielding material may affect the amount by whichthe resonant frequency shifts (e.g., changes) because the thickness ofthe shielding material determines the magnetic reluctance of themagnetic shield, and the reluctance of the magnetic shield also, and thepermeability of the shielding material also affects the inductance ofinductive sensor 182. The thinner the shielding material, the lessvolume of permeable material there is to affect the inductance ofinductive sensor 182. Accordingly, the shielding material should be athin as is practical for design needs.

For ferrite thickness of 0.2 mm, the change in the resonant frequencyfrom the baseline frequency may be approximately 40 kHz, and for ferritethickness of 0.05 mm, the change in resonant frequency from the baselineresonant frequency may be approximately 6 kHz. Examples of the shieldingmaterial include 3M Flux Field Directional Material (FDM) numberEM15TF-007 or Larid MULL6060-300, both have a thickness of 0.05 mm andexhibit good results. Moreover, having shielding material may bebeneficial because the resonant frequency of the electronic circuit ofinductive sensor 182 may not shift or the shift may be greatly reducedwhen fall protection device is flexed or laterally compressed. It shouldbe understood that inclusion of the example shielding material isprovided for as one example and should not be considered as arequirement for all examples.

In some examples, fall protection device 11A includes a plurality ofinductive sensors, similar to inductive sensor 182. For example, it ispossible that a support structure may be within the area of attachmentof fall protection device 11A but the resonant frequency of inductivesensor 182 does not change because the support structure is notsufficiently proximate to inductive sensor 182. By including multipleinductive sensors, similar to inductive sensor 182, in fall protectiondevice 11A, the overall sensitivity of sensing that a support structureis within the area of attachment increases. In examples where there area plurality of inductive sensors, the inductive sensing processor maysequentially determine the resonant frequency of each of the inductivesensors to prevent interactions, such as magnetic field interactions,between the inductive sensors.

FIG. 8 is a conceptual diagram illustrating an example of a plurality ofinductive sensors of a fall protection device. As illustrated in FIG. 8, fall protection device 11A includes inductive sensors 182A and 182B,which are substantially similar, including identical, to inductivesensor 182. For example, inductive sensor 182A includes coils 190A and190B, which are substantially similar, including identical, to coils184A and 184B. Similarly, inductive sensor 182B includes coils 192A and192B, which are substantially similar, including identical, to coils184A and 184B. Fall protection device 11A may include more than twoinductive sensors.

By having a plurality of inductive sensors, the resonant frequency ofone or more of the inductive sensors may shift based on the location ofthe support structure within the area of attachment. For example, if thesupport structure is proximate to inductive sensor 182A, then theresonant frequency of the electronic circuit of inductive sensor 182Amay shift more than the resonant frequency of the electronic circuit ofinductive sensor 182B, and vice-versa. As described above, with respectto FIGS. 4A and 4B, processors 100 may determine the amount by which theresonant frequency of both inductive sensors 182A and 182B shifted, sumthe amounts together, and determine whether the support structure iswithin the area of attachment based on the summed value. As describedabove, with respect to FIG. 15 , processors may determine a rate ofchange in the resonant frequency of inductive sensors 182A and 182B, anddetermine whether the support structure is within the area of attachmentbased on the rate of change in the resonant frequencies.

As illustrated in FIG. 8 , inductive sensor 182A and inductive sensor182B are separated by a distance “d.” As one example, the distance d isapproximately less than 10 mm, such as 3 mm. However, because there is aseparation between inductive sensors 182A and 182B, the overallsensitivity of determining whether a support structure is within thearea of attachment may be reduced. For example, if the support structureis located predominantly between inductive sensors 182A and 182B, theresonant frequencies of the electronic circuits of inductive sensors182A and 182B may not change sufficiently, which may cause processors100 to determine that the support structure is not within the area ofattachment. To eliminate the gap, adjacent inductive sensors may overlapone another, as illustrated in FIG. 9 .

FIG. 9 is a conceptual diagram illustrating another example of aplurality of inductive sensors of a fall protection device. Asillustrated in FIG. 9 , inductive sensor 182A partially overlapsinductive sensor 182B, shown with dashed lines. For example, inductivesensor 182A may be formed on a first higher layer of PCB 188, andinductive sensor 182B may be formed on a second lower layer of PCB 188(e.g., other side of PCB 188 relative to where inductive sensor 182A islocated), and partially beneath inductive sensor 182A. In some examples,PCB 188 may include four layers, where coils 190A and 190B are ondifferent layers, and 192A and 192B are on different layers, andinductive sensors 182A and 182B are on different layers.

However, there may be a possibility that inductive sensors 182A and 182Bmagnetically couple with one another in the example of FIG. 9 . Toprevent such coupling, the amount of overlap may be selected to minimizethe coupling. For example, magnetic coupling from inductive sensor 182Ato inductive sensor 182B may have a coefficient between +1 and −1 basedon geometric configuration. The coefficient is indicative of the amountof coupling between sensors 182A and 182B. In some examples, thegeometric configuration is selected such that the magnetic couplingcoefficient is approximately zero to minimize the magnetic coupling. Oneway to select the geometric configuration such that the magneticcoupling coefficient is zero is by trial-and-error (e.g., by testing twoexample PCBs 188, exciting one, and measuring magnetic coupling on theother). For example, multiple PCBs 188 may be formed with inductivesensors 182A and 182B having different amounts of overlap. The PCB thatresults in the smallest magnetic coupling coefficient may be selected asthe PCB 188 that is placed within fall protection device 11A fordetermining whether a support structure is within the area ofattachment.

FIGS. 7-9 illustrate examples of inductive sensors 182. In someexamples, in addition to inductive sensors 182, fall protection devices11 may include addition coils. For example, fall protection devices 11includes a plurality of inductive sensors 182 on a flexible PCB. Inaddition, fall protection devices 11 may include additional sets of oneor more coils. One example of such an additional coil is a magnet wirewound on a curved ferrite core, with the curve following the curve ofthe inductive sensors 182. The axis of the coil is approximately normalto the axis of inductive sensors 182. The use of such additional coilsmay be useful for detection of looped support structures such asD-rings.

FIG. 10 illustrates an example of a snap hook 220 that is configured inaccordance with aspects of this disclosure. While the exampleillustrated in FIG. 10 comprises a snap hook, it should be understoodthat the techniques described herein may be applied to a variety ofother devices for securing a user to an anchor, such as a carabiner. Forexample, a carabiner may be constructed similarly to snap hook 220, butmay rely on a rotating or self-locking gate mechanism instead of theplanar lock mechanism shown in FIG. 10 .

The example snap hook 220 of FIG. 10 includes a moveable gate 222 and abody 224 that generally defines an area of attachment 226 within which asupport structure is disposed when snap hook 220 is connected to thesupport structure. Snap hook 220 includes bowl 228, which includes theportion of snap hook 220 that curves around and is openable to receivethe support structure within area of attachment 226. Snap hook 220 alsoincludes sensors 230A and 230B (collectively sensors 230), which areillustrated as being located within bowl 228, computing device 234, andlock 238. Snap hook 220 may be attached to, for example, an energyabsorbing lanyard, a self-retracting lanyard, or another device viaattachment point 240.

Moveable gate 222 moves between an open position and a closed position.The example of FIG. 10 illustrates moveable gate 222 in the closedposition such that moveable gate 222 contacts body 224 and creates acontinuous loop that defines area of attachment 226. In the openposition, moveable gate 222 pivots inward toward area of attachment 226and allows a support structure to be moved into area of attachment 226.

One or more sensors 230, which may be examples of inductive sensors 182of FIGS. 7-9 , may be configured to sense whether a material (such as asupport structure) is disposed within area of attachment 226. In theillustrated example, a resonant frequency of sensors 230 changes when ametal structure is within an electromagnetic field created by sensors182 within area of attachment 226. As described herein, inductive sensor230 may be positioned and oriented, e.g., as shown in the example ofFIG. 10 , to cause the electromagnetic field to be generated within thearea of attachment 226. Examples of one or more sensors 230 areillustrated in FIGS. 7-9 .

As illustrated, sensor 230A includes set of coils 231A and set of coils231B. Sensor 230B includes set of coils 231C and set of coils 231B.Coils 231A and 231C may be similar to coils 184A, and set of coils 231Band 231D may be similar to coils 184B. When current flows through theelectronic circuits of sensors 230A and 230B, the electronic circuitsmay generate electromagnetic fields within area of attachment 226 asillustrated with dashed lines 225A and 225B. The arrows in the dashedlines are shown to illustrate direction, and should not be consideredlimiting. The electromagnetic field (also called “flux”) extends fromcoils 231B to coils 231A, and similarly from coils 231C to 231D. FIG. 10illustrates a portion of the complete field, and the field is largeenough to encompass area of attachment 226.

In some examples, the electromagnetic fields may alternate betweensensors 230A and 230B. For example, sensor 230A may generate theelectromagnetic field, and then sensor 230B may generate theelectromagnetic field. Accordingly, in some examples, the both lines225A and 225B need not necessarily be present at the same time, and mayalternate.

In some examples, in addition to inductive sensors 230, snap hook 220may include an additional coil such as a magnet wire wound on a curvedferrite core. The curve of the wound coil may be the same through bowl228 (e.g., with the curve following the curve of the sensors 230). Theaxis of the coil is approximately normal to the axis of inductivesensors 182. The use of such additional coils may be useful fordetection of looped support structures such as D-rings.

Although not shown, snap hook 220 includes one or more gate movementsensors that may be configured to generate data that indicates movementof gate 222. For example, the gate movement sensors may be configured togenerate a signal that indicates that gate 222 has been moved from theclosed position to the open position or vice versa. In some examples,the gate movement sensors may output a discrete signal (e.g., a signalthat indicates whether gate 222 is in the open position or closedposition). In other examples, the gate movement sensors may output dataindicative of a relative position of gate 222. The gate movement sensorsmay include any sensor capable of generating an output based on aposition or movement of gate 222, such as one or more switches, rotaryencoders, accelerometers, or the like.

Computing device 234 may include computing components responsible forprocessing and/or transmitting data generated by one or more sensors 230and the gate movement sensors. Computing device 234 may also include apower source, such as a battery. In some examples, computing device 234may be configured to include the components of computing device 98 shownin FIG. 3 . In other examples, computing device 234 may include a subsetof computing device 98. For example, computing device 234 may simplyinclude one or more processors and a communication unit for transmittingdata from one or more sensors 230 and the gate movement sensors toanother computing device.

Although not shown, snap hook 220 may include a primary lockingmechanism that is configured to prevent gate 222 from being moved to theopen position. For example, the primary locking mechanism includes acomponent that engages with gate 222 to prevent gate 222 from pivotingtoward area of attachment 226. When a user operates the primary lockingmechanism, the component of the primary locking mechanism disengagesfrom gate 222 to allow gate to be moved toward area of attachment 226.

In some examples, lock 238 may be configured to impede or prevent gate222 from being moved from a closed position to an open position based ona connection status of snap hook 220, thereby impeding or preventingsnap hook 220 from being disconnected from a support structure. Forexample, computing device 234 (and/or another computing device incommunication with snap hook 220) may determine whether snap hook 220 isconnected to a support structure based on electrical characteristics ofone or more sensors 230. That is, computing device 234 may receive data(e.g., from the inductive sensing processor) indicating resonantfrequencies of one or more sensors 230 from which computing device 234may determine whether a support structure is present within area ofattachment 226. For instance, computing device 234 performs the exampleoperations described above with respect to FIGS. 4A and 4B and/or FIG.15 to determine whether a support structure is within area of attachment226. Computing device 234 may determine a connection status based onsuch data. For example, computing device 234 may determine that snaphook 220 is connected when the support structure is present and gate 222is closed.

Computing device 234 may also or alternatively use data from the gatemovement sensors to determine the connection status. For example,computing device 234 may determine that snap hook 220 has been connectedto a support structure based on a number of ordered operations. In thisexample, computing device 234 may receive data from the gate movementsensors that indicates that gate 222 has moved to an open position.Computing device 234 may receive data from one or more sensors 230indicating that a support structure is disposed within area ofattachment 226. Computing device 234 may then receive data from the gatemovement sensors that indicates that gate 222 has moved to a closedposition and determine that snap hook 220 has been connected to thesupport structure.

In one example, computing device 234 periodically activates one or moresensors 230 to determine whether a metal structure is disposed withinarea of attachment 226. In one example, computing device 234 may operateone or more sensors 230 based on data from the gate movement sensors.For example, upon receiving data from the gate movement sensors thatgate 222 has moved to an open position, computing device 234 maydetermine the resonant frequencies of one or more sensors 230 in orderto determine whether a metal support structure is within area ofattachment 226.

After determining that snap hook 220 has been connected to a supportstructure, computing device 234 (or another computing device incommunication with snap hook 220) may monitor the status of one or moreother articles of fall protection equipment being used by the same user(referred to herein as a set of fall protection equipment). For example,computing device 234 may identify when the other articles of fallprotection equipment are connected to and disconnected from one or moresupport structure, e.g., as a worker moves throughout a worksite.Computing device 234 may determine when snap hook 220 is the onlyarticle of fall protection equipment in the set that is connected to thesupport structure. Based on this determination, computing device 234 mayactivate lock 238 in order to impede or prevent gate 222 from beingmoved from a closed position to an open position based on a connectionstatus of snap hook 220, thereby impeding or preventing snap hook 220from being disconnected from a support structure.

In some examples, lock 238 may include a locking component thatinterfaces directly with gate 222 in order to prevent gate 222 frombeing opened. For example, lock 238 may include a mechanical barrierthat prevents gate 222 from moving. In other examples, lock 238 may beconfigured to interface with one or more other locking mechanisms ofsnap hook 220, such as the primary locking mechanism. For example, lock238 may include a mechanical barrier that prevents (e.g., restricts) theprimary locking mechanism from moving, thereby preventing gate 222 frommoving.

While the example described with respect to FIG. 10 includes the primarylocking mechanism and lock 238, other examples may include additionallocking mechanisms. For example, certain safety standards or codes mayrequire at least two separate and deliberate actions for gate 222 toopen, thereby allowing snap hook 220 to connect to or disconnect from asupport structure. Each separate and deliberate action may be associatedwith a locking mechanism. Example locking mechanisms for snap hook 220may include latches, spring loaded collars, levers, or any combinationof other components that require a deliberate action on the part of theuser to operate. According to aspects of this disclosure, lock 238 maybe a tertiary locking mechanism that is included in addition to thelocking mechanisms associated with the two separate and deliberateactions.

Computing device 234 may also release lock 238. For example, computingdevice 234 may continue to monitor whether fall protection devices inthe set is connected to the support structure. In the event that one ormore other articles of fall protection devices are connected to thesupport structure, computing device 234 may release lock 238 such thatlock 238 no longer impedes snap hook 220 from being disconnected fromthe support structure. Additionally or alternatively, lock 238 mayinclude a manual override that allows a user to manually release lock238.

In the event that computing device 234 actuates lock 238, computingdevice 234 may generate a signal that indicates lock 238 has beenactuated and/or that lock 238 has been manually overridden. In someexamples, computing device 234 may generate an electronic message, anaudible output, a visual output, and/or tactile output that indicatesthat lock 238 has been activated and/or a manual override has beenperformed.

It should be understood that the architecture and arrangement of snaphook 220 illustrated in FIG. 10 is shown for exemplary purposes only. Inother examples, snap hook 220 may be configured in a variety of otherways having additional, fewer, or alternative components than thoseshown in FIG. 10 . For example, as noted above, snap hook 220 may beconfigured to include only a subset of components, such as one or moresensors 230, the gate movement sensors, and a communication unit fortransmitting data to another computing device, such as one of hubs 14,for performing certain processing functions.

In another example, snap hook 220 may include a feedback component forindicating a connection status of snap hook 220. For example, thefeedback component may comprise any variety of speakers, displays,lights, haptic feedback components, or the like to generate an audiblealert, a visual alert, or a tactile alert in response to determiningthat the gate of snap hook 220 is opened when snap hook 220 is the onlyarticle of fall protection connected to a support structure. In the casewhere a worker is using two snap hooks (e.g., two of snap hooks 220) forfall protection, a computing device may determine that a first snap hookis connected to a support structure and its gate is closed, while asecond snap hook is not connected to a support structure. If thecomputing device determines that the gate of the first snap hook isopened while the second snap hook is not connected to the supportstructure, then the computing device may cause the feedback component toindicate a connection status, provide an alert, or output any otheroutput that may be discernable by the worker. Further examples aredescribed in FIG. 14 and throughout this specification.

In some examples, snap hook 220 may be in a safe operation; however,snap hook 220 may lose detection of the support structure to which it isattached although the gate of snap hook 220 may not have opened. Theloss of detection of snap hook 220 may occur due to physical propertiesor other physical material on the support structure and/or snap hook 220that impairs the detection of the support structure by snap hook 220, ordue to subsequent movement of the hook such that the support structuremay have moved away from the detection area of the sensor. For instance,the property or physical material may be rust, insulators, or othermaterial that impairs detection of the support structure by snap hook220. If detection of the support structure by snap hook 220 is impairedor completely undetected but snap hook 220 is in a safe state and thegate of snap hook 220 has not been opened, then one or more processorsassociated with snap hook 220 may determine that snap hook 220 is stillin safe operation although the support structure is not detected. Inthis way, even if the support structure is not detected for snap hook220 but snap hook 220 is in safe operation because the gate of snap hook220 was not opened since entering safe operation, the one or moreprocessors associated with smart hook 220 will not determine snap hook220 is an unsafe operation.

In some examples, one or more processors associated with snap hook 220that determine the state of snap hook 220 may determine a statetransition condition has occurred for a pre-defined time duration beforetransitioning from one state to another state. For instance, a statetransition condition (e.g., “Anchor && Gate Open”) may be required bythe one or more processors to be true, exist, or otherwise be detectedfor the pre-defined time duration before the one or more processorsdetermine that snap hook 220 has transitioned to the next statetransition for the state transition condition.

In other examples, the one or more processors associated with snap hook220 may, upon detecting a state transition condition, ignore otherdetected state transition conditions that occur within a pre-definedtime duration after the state transition condition is detected. Thistechnique may ensure the system transitions to a next state afterdetection of the state transition condition rather than remaining in thecurrent state by ignoring any state change transitions that are detectedduring the pre-defined time duration and which would otherwise cause thesystem to remain in the current state.

In some examples, multiple snap hooks may be used together in a system.For instance, snap hook 220 may be used in a system as a first snap hooktogether with a second snap hook. In some examples, each of the firstand second snap hooks may be included as part of an article of personalprotection equipment. The personal protection equipment may be worn by asingle worker and the worker may, in some examples, operate the firstsnap hook with the worker's first hand and the worker may operate thesecond snap hook with the worker's other, second hand. Each of the firstand second snap hooks may be communicatively coupled to one or moreprocessors that receive first and second data respectively from thefirst and second smart hooks. The one or more processors may be includeda part of an article of personal protection equipment, a mobilecomputing device associated with the worker, or a remote computingdevice that is separate from the worker, personal protection equipment,and/or smart hooks. As described herein, the one or more processors mayperform one or more operations based at least in part on the first dataand the second data, such as but not limited to, generating alerts,processing the data, or sending the data to other computing devices.

In some examples, the first snap hook may be a first fall protectiondevice comprising an inductive sensor having an electronic circuit andthe second snap hook may be a second fall protection device comprisingan inductive sensor having an electronic circuit. One or more processorsin communication with the first fall protection device and the secondfall protection device may determine that the first fall protectiondevice is in an unsafe operation and the second fall protection deviceis in a safe operation. The one or more processors may determine that agate of the second fall protection device is opened. The one or moreprocessors may determine, based at least in part on the determinationthat the gate of the second fall protection device is opened, that thesecond fall protection device is in a sub-optimal operation. The one ormore processors may generate, in response to the determination that thesecond fall protection device is in the sub-optimal operation,information indicating sub-optimal operation of the second fallprotection device, wherein the information comprises at least one ofaudible, visual, or haptic information.

In some examples, the one or more processors may determine that thefirst fall protection device is in an unsafe operation and the secondfall protection device is in a safe operation. The one or moreprocessors may determine that the support structure is not within anarea of attachment of the second fall protection device. The one or moreprocessors may determine, based at least in part on the determinationthat the support structure is not within an area of attachment of thesecond fall protection device, that the second fall protection device isin an unsafe operation. In some examples, the one or more processors maygenerate, in response to the determination that the second fallprotection device is in the unsafe operation, information indicatingunsafe operation of the second fall protection device, wherein theinformation comprises at least one of audible, visual, or hapticinformation.

In still another example, snap hook 220 may include one or morecomponents for determining whether a fall has occurred, such as a fallsensor not shown. For example, the fall sensor may comprise a switch,sensor, or the like for determining a fall condition. In one example,the fall sensor may determine deflection, movement, or motion ofattachment point 240 to which a line constituent is attached in responseto a load. If the load exceeds a predetermined threshold, the fallsensor (which may include hall-effect sensors, mechanical switches, orthe like) may determine relative movement or a change in shape ofattachment point 240.

In addition to generating a signal in the event that attachment point240 (or another component located near the lower portion of snap hook220) moves a predetermined amount in response to a given load, theposition can also be monitored via sensors for a duration of time toindicate that a specific load has not only been applied to the connectorbut also applied for a duration. Based on such data, snap hook 220 (orcomputing device 98) may determine that a user has fallen (therebygenerating the load), but is also suspended post fall.

Based on data from the fall sensor, snap hook 220 (or another device,such as computing device 98) may generate one or more alerts. Forexample, upon determining that a fall has occurred, the fall sensor maygenerate an audible, visual, or wireless communication (e.g., electronicmessage) that indicates that the fall has occurred.

FIG. 11 illustrates an example of a carrier sleeve 260 that isconfigured in accordance with aspects of this disclosure. The examplecarrier sleeve 260 of FIG. 11 includes a moveable gate 262 and a gate264 that generally defines an area of attachment 266 within which asupport structure is disposed when carrier sleeve 260 is connected tothe support structure, e.g., a vertically disposed cable that runsthrough area of attachment 266. Carrier sleeve 260 also includesinductive sensor housing 268 having one or more inductive sensors 270,sensor 272, computing device 274, primary locking mechanism 276,secondary locking mechanism 278 and lock 280.

Moveable gate 262 moves between an open position and a closed position.The example of FIG. 11 illustrates moveable gate 262 in the closedposition such that moveable gate 262 is positioned proximate to gate 264such that area of attachment 266 is a closed space that prevents acarrier from moving into or out of area of attachment 266. In the openposition, moveable gate 262 pivots toward gate 264 and allows a supportstructure to be moved into area of attachment 266.

A resonant frequency of one or more sensors 270 may change when metal isdisposed within area of attachment 266. For example, even withoutcontact with one or more sensors 270, metal being disposed within areaof attachment 266 may cause the resonant frequency of one or moresensors 270 to change, indicating that a suitable support structure iswithin the area of attachment 266. One or more sensors 270 may besimilar to sensors 182 illustrated in FIGS. 7-9 .

Sensor 272 may be configured to generate data that indicates movement ofgate 262. For example, sensor 272 may be configured to generate a signalthat indicates that gate 262 has been moved from the closed position tothe open position or vice versa. In some examples, sensor 272 may outputa discrete signal (e.g., a signal that indicates whether gate 262 is inthe open position or closed position). In other examples, sensor 272 mayoutput data indicative of a relative position of gate 262. Sensor 272may include any sensor capable of generating an output based on aposition or movement of gate 262, such as one or more switches, rotaryencoders, accelerometers, or the like.

Computing device 274 may include computing components responsible forprocessing and/or transmitting data generated by one or more sensors 270and sensor 272. Computing device 274 may also include a power source,such as a battery. In some examples, computing device 274 may beconfigured to include the components of computing device 98 shown inFIG. 3 . In other examples, computing device 274 may include a subset ofcomputing device 98. For example, computing device 274 may simplyinclude one or more processors and a communication unit for transmittingdata from one or more sensors 270 and sensor 272 to another computingdevice.

Primary locking mechanism 276 is configured to prevent gate 262 frombeing moved to the open position. For example, primary locking mechanism276 includes a component that engages with gate 262 to prevent gate 262from moving to the open position. When a user operates primary lockingmechanism 276 (e.g., a user rotates or otherwise moves primary lockingmechanism 276) the component of primary locking mechanism 276 disengagesfrom gate 262.

Secondary locking mechanism 278 is also configured to prevent gate 262from being moved to the open position. For example, secondary lockingmechanism 278 includes a spring component that prevents gate 262 frommoving to the open position without a deliberate action by a user ofcarrier sleeve 260. When a user operates secondary locking mechanism 278(e.g., a user presses secondary locking mechanism 278 to bias thespring) gate 262 moves to provide access to area of attachment 266.

In some examples, lock 280 may be configured to impede or prevent gate262 from being moved from a closed position to an open position based ona connection status of carrier sleeve 260, thereby impeding orpreventing carrier sleeve 260 from being disconnected from a supportstructure. For example, computing device 274 (and/or another computingdevice in communication with carrier sleeve 260) may determine whethercarrier sleeve 260 is connected to a support structure based on resonantfrequencies of one or more sensors 270. That is, computing device 274may perform the example operations described above with respect to FIGS.4A and 4B and/or FIG. 15 with one or more sensors 270 to determinewhether a support structure is present within area of attachment 266.Computing device 274 may determine a connection status based on suchdata. For example, computing device 274 may determine that carriersleeve 260 is connected when the support structure is present anddisconnected when the support structure is not present.

In some examples, computing device 274 may also or alternatively usedata from sensor 272 to determine the connection status. For example,computing device 172 may determine that carrier sleeve 260 has beenconnected to a support structure based on a number of orderedoperations. In this example, computing device 274 may receive data fromsensor 272 that indicates that gate 262 has moved to an open position.Computing device 274 may the receive data from first sensor 168indicating that a support structure is disposed within area ofattachment 266. Computing device 274 may then receive data from sensor272 that indicates that gate 262 has moved to a closed position anddetermine that carrier sleeve 260 has been connected to the supportstructure.

After determining that carrier sleeve 260 has been connected to asupport structure, computing device 274 (or another computing device incommunication with carrier sleeve 260) may monitor the status of one ormore other articles of fall protection devices 11 being used by the sameuser (referred to herein as a set of fall protection equipment). Forexample, computing device 274 may identify when the other articles offall protection devices 11 (such as one or more snap hooks 220 (FIG. 10)) are connected to and disconnected from one or more support structure,e.g., as a worker moves throughout a worksite. Computing device 274 maydetermine when carrier sleeve 260 is the only article of fall protectionequipment in the set that is connected to the support structure. Basedon this determination, computing device 274 may activate lock 280 inorder to impede or prevent gate 262 from being moved from a closedposition to an open position based on a connection status of carriersleeve 260, thereby impeding or preventing carrier sleeve 260 from beingdisconnected from a support structure.

In some examples, as described with respect to the example of FIG. 12below, lock 280 may include a locking component that interfaces directlywith gate 262 in order to prevent gate 262 from being opened. Forexample, lock 280 may include a mechanical barrier that prevents gate262 from moving. In other examples, lock 280 may be configured tointerface with one or more other locking mechanisms of carrier sleeve260, such as primary locking mechanism 276 or secondary lockingmechanism 278. For example, lock 280 may include a mechanical barrierthat prevents primary locking mechanism 276 from being moved or rotated,thereby preventing gate 262 from moving.

In some examples, computing device 274 may also release lock 280. Forexample, computing device 274 may continue to monitor whether fallprotection equipment in the set is connected to the support structure.In the event that one or more other articles of fall protectionequipment are connected to the support structure, computing device 274may release lock 280 such that lock 280 no longer impedes carrier sleeve260 from being disconnected from the support structure. Additionally oralternatively, lock 280 may include a manual override that allows a userto manually release lock 280.

In the event that computing device 274 actuates lock 280, computingdevice 274 may generate a signal that indicates lock 280 has beenactuated and/or that lock 280 has been manually overridden. In someexamples, computing device 274 may generate an electronic message, anaudible output, a visual output, and/or tactile output that indicatesthat lock 280 has been activated and/or a manual override has beenperformed.

It should be understood that the architecture and arrangement of carriersleeve 260 illustrated in FIG. 11 is shown for exemplary purposes only.In other examples, carrier sleeve 260 may be configured in a variety ofother ways having additional, fewer, or alternative components thanthose shown in FIG. 11 . For example, as noted above, carrier sleeve 260may be configured to include only a subset of components, such as one ormore sensors 270, sensor 272, and a communication unit for transmittingdata to another computing device, such as one of hubs 14, for performingcertain processing functions.

In another example, carrier sleeve 260 may include a feedback componentfor indicating a connection status of carrier sleeve 260. For example,the feedback component may comprise any variety of speakers, displays,lights, haptic feedback components, or the like to generate an audiblealert, a visual alert, or a tactile alert in response to determiningthat carrier sleeve 260 is the only article of fall protection connectedto a support structure.

In still another example, carrier sleeve 260 may include one or morecomponents for determining whether a fall has occurred, such as fallsensor 282. For example, according to aspects of this disclosure, fallsensor 282 may comprise a switch, sensor, or the like for determining afall condition. In one example, fall sensor 282 may determinedeflection, movement, or motion of a component that attaches carriersleeve 260 to a user in response to a load. If the load exceeds apredetermined threshold, fall sensor 282 (which may include hall-effectsensors, mechanical switches, or the like) may determine relativemovement or a change in shape of the attachment component. In otherexamples, fall sensor 282 may be positioned anywhere on carrier sleeve260 that allows fall sensor 282 to determine a change in load to acomponent that attaches carrier sleeve 260 to a user.

In addition to generating a signal in the event that an attachmentcomponent moves a predetermined amount in response to a given load, theposition can also be monitored via sensors for a duration of time toindicate that a specific load has not only been applied to the connectorbut also applied for a duration. Based on such data, carrier sleeve 260(or computing device 98) may determine that a user has fallen (therebygenerating the load), but is also suspended post fall.

Based on data from fall sensor 282, carrier sleeve 260 (or anotherdevice, such as computing device 98) may generate one or more alerts.For example, upon determining that a fall has occurred, fall sensor 282may generate an audible, visual, or wireless communication (e.g.,electronic message) that indicates that the fall has occurred.

FIG. 12 illustrates an example carrier sleeve 260 in greater detail. Forexample, as described above, lock 280 may be configured to impede orprevent gate 262 from being moved from a closed position to an openposition based on a connection status of carrier sleeve 260, therebyimpeding or preventing carrier sleeve 260 from being disconnected from asupport structure. In the example of FIG. 12 , lock 280 includes asolenoid 282 that moves a pin 284 from an extended position 286 to aretracted position 288 and vice versa.

For example, as described above with respect to FIG. 11 , computingdevice 274 may determine when carrier sleeve 260 is the only article offall protection equipment in the set that is connected to the supportstructure. Based on this determination, computing device 274 mayactivate lock 280. Upon activating lock 280, pin 284 may move fromretracted position 288 to extended position 286. When in extendedposition 286, pin 284 may prevent gate 262 from moving from a closedposition to an open position. In some examples, pin 284 may directlyinterface with gate 262 to prevent gate 262 from being opened. In otherexamples, pin 284 may interface with another component of carrier sleeve260 (such as primary locking mechanism 276 or secondary lockingmechanism 278) to prevent gate 262 from being opened.

In some examples, computing device 274 may also release lock 280. Forexample, computing device 274 may continue to monitor whether fallprotection equipment in the set is connected to the support structure.In the event that one or more other articles of fall protectionequipment are connected to the support structure, computing device 274may release lock 280 by sending a signal to solenoid 282 to move pin 284from extended position 286 to retracted position 288. Additionally oralternatively, lock 280 may include a manual override that allows a userto manually move pin 284 from extended position 286 to retractedposition 288.

FIG. 13 illustrates an example of one of hubs 14 in greater detail. Forexample, hub 14 includes one or more processors 300, memory 302 that maystore usage data 304, connection data 306, and alert data 308,communication unit 310, sensors 312, user interface 314, and remoteinterface 316. It should be understood that the architecture andarrangement of hub 14 illustrated in FIG. 13 is shown for exemplarypurposes only. In other examples, hub 14 may be configured in a varietyof other ways having additional, fewer, or alternative components thanthose shown in FIG. 13 . For example, hub 14 may also include one ormore batteries, charging components, or the like not shown in FIG. 13 .In addition, while shown as a wearable device in the example of FIG. 13, in other examples, hub 14 may be implemented as stand-alone devicedeployed in a particular environment.

In general, hub 14 may enable and facilitate communication between fallprotection device 11A and PPEM 6. Examples of fall protection device 11Ainclude snap hook 220 or carrier sleeve 260. For ease, FIG. 13illustrates fall protection device 11A. Other example fall protectiondevices 11 may operate in a substantially similar manner.

Fall protection device 11A as well as other PPEs for a respective workermay communicate with hub 14 via Bluetooth or other short range protocol,and hub 14 may communicate with PPEMs 6 via wireless communications,such as via 802.11 WiFi protocols, or the like. In some examples, hub 14may also control one or more components of fall protection device 11A(e.g., such as locks) based on connection data 306, generate and/oroutput alerts, or perform a variety of other functions.

Processors 300, in one example, are configured to implementfunctionality and/or process instructions for execution within hub 14.For example, processors 300 may be capable of processing instructionsstored by memory 302. Processors 300 may include, for example,microprocessors, digital signal processors (DSPs), application specificintegrated circuits (ASICs), field-programmable gate array (FPGAs), orequivalent discrete or integrated logic circuitry.

Memory 302 may include a computer-readable storage medium orcomputer-readable storage device. In some examples, memory 302 mayinclude one or more of a short-term memory or a long-term memory. Memory302 may include, for example, random access memories (RAM), dynamicrandom access memories (DRAM), static random access memories (SRAM),magnetic hard discs, optical discs, flash memories, or forms ofelectrically programmable memories (EPROM) or electrically erasable andprogrammable memories (EEPROM).

In some examples, memory 302 may store an operating system (not shown)or other application that controls the operation of components of hub14. For example, the operating system may facilitate the communicationof data from memory 302 to communication unit 310. In some examples,memory 302 is used to store program instructions for execution byprocessors 300. Memory 302 may also be configured to store informationwithin hub 14 during operation. In the example shown in FIG. 13 , memory302 may store usage data 304, connection data 306, and/or alert data308, as described in greater detail below.

Hub 14 may use communication unit 310 to communicate with externaldevices via one or more wired or wireless connections. Communicationunit 310 may include various mixers, filters, amplifiers and othercomponents designed for signal modulation, as well as one or moreantennas and/or other components designed for transmitting and receivingdata. Communication unit 310 may send and receive data to othercomputing devices using any one or more suitable data communicationtechniques. Examples of such communication techniques may includeTCP/IP, Ethernet, Wi-Fi, Bluetooth, 4G, LTE, to name only a fewexamples. For example, communication unit 310 may communicate with fallprotection device 11A or other PPE via Bluetooth or other short rangeprotocol, and communication unit 310 may communicate with PPEMs 6 viawireless communications, such as via 802.11 WiFi protocols, or the like.

Sensors 312 may include one or more sensors that generate dataindicative of an activity of a worker 10 associated with hub 14 and/ordata indicative of an environment in which hub 14 is located. Sensors312 may include, as examples, one or more accelerometers, one or moresensors to detect conditions present in a particular environment (e.g.,sensors for measuring temperature, humidity, particulate content, noiselevels, air quality, or any variety of other characteristics ofenvironments in which fall protection device 11A may be used), or avariety of other sensors.

User interface 314 may include one more user interface devicesincluding, as examples, a variety of lights, displays, haptic feedbackgenerators, speakers or the like. In general, user interface 314 mayoutput a status of fall protection device 11A and/or hub 14, as well asany alerts for worker 10. In one example, user interface 314 may includea plurality of multi-color LEDs that illuminate to provide informationto worker 10. In another example, user interface 314 may include a motorthat is configured to vibrate hub 14 to provide haptic feedback toworker 10.

Remote interface 316 is configured to generate data for output atclients 62 (FIG. 2 ). For example, remote interface 316 may generatedata indicative of a status of fall protection device 11A and/or hub 14.For example, remote interface 316 may generate data that indicateswhether fall protection device 11A is connected to hub 14 and/orinformation about components of fall protection device 11A. That is,remote interface 316 may generate data indicative of, as examples,remaining service life of fall protection device 11A, a status of abattery of fall protection device 11A, a connection status of fallprotection device 11A, whether fall protection device 11A is the onlyfall protection equipment connected to a support structure, whether auser has performed a manual override of a lock of fall protection device11A, whether maintenance or replacement of fall protection device 11A isneeded, or the like. Remote interface 316 may additionally oralternatively generate data that is indicative of any alerts issued byhub 14.

According to aspects of this disclosure, hub 14 may store usage data 304from sensors of fall protection device 11A. Usage data 304 generallyrefers to data that is indicative of the manner in which a user usesfall protection device 11A including, as examples, data that indicates arelative position of a component of fall protection device 11A, datathat is indicative of whether a support structure is disposed within anarea of attachment of fall protection device 11A, or other operations orcharacteristics of fall protection device 11A.

As described herein, electrical characteristics, such as resonantfrequencies of sensors of fall protection device 11A may indicateoperation of fall protection equipment 11 and an inductive sensingprocessor determines the resonant frequency and transmits dataindicating the resonant frequency in real-time or near real-time to hub14. In some examples, hub 14 may immediately relay usage data 304 toanother computing device, such as PPEMS 6, via communication unit 310.In other examples, memory 302 may store usage data 304 for some timeprior to uploading the data to another device. For example, in someinstances, communication unit 310 may be able to communicate with fallprotection device 11A but may not have network connectivity, e.g., dueto an environment in which fall protection device 11A is located and/ornetwork outages. In such instances, hub 14 may store usage data 304 tomemory 302, which may allow the usage data to be uploaded to anotherdevice upon a network connection becoming available.

According to aspects of this disclosure, hub 14 also stores connectiondata 306 that indicates a connection status of fall protection device11A used by worker 10. That is, connection data 306 may indicate whetherfall protection device 11A in a set of fall protection devices beingused by worker 10 are connected to a support structure. In someinstances, hub 14 may receive connection data 306 from fall protectiondevice 11A, e.g., as determined by fall protection device 11A. In otherexamples, hub 14 may receive data from sensors of fall protection device11A and processors 300 may determine connection data 306 based on thereceived sensor data.

According to aspects of this disclosure, hub 14 may control theoperation of fall protection device 11A based on connection data 306.For example, hub 14 may determine, based on connection data 306, thatfall protection device 11A has been connected to a support structure.Hub 14 may also determine when one or more articles of fall protectiondevice 11A have been disconnected from a support structure. Hub 14 maydetermine when a particular article of fall protection device 11A is theonly article of fall protection device 11A in a set that is connected toa support structure. Based on this determination, in some examples, hub14 may issue an audible, visual, or tactile alert (e.g., via userinterface 314) or transmit an electronic message (e.g., via remoteinterface 316) that indicates that fall protection device 11A is theonly article of fall protection equipment connected to the supportstructure. In other examples, hub 14 may activate a lock of fallprotection equipment in order to impede or prevent fall protectionequipment from being disconnected from the support structure.

Hub 14 may store alert data 308 for generating alerts for output by userinterface 314 and/or remote interface 316. For example, hub 14 mayreceive alert data from PPEMS 6, fall protection device 11A, end-usercomputing devices 16, remote users using computing devices 18, safetystations 15, or other computing devices. In some examples, the alertdata may be based on operation of fall protection device 11A. Forexample, hub 14 may receive alert data 308 that indicates that fallprotection device 11A is the only article of fall protection equipmentconnected to the support structure. As another example, hub 14 mayreceive alert data 308 that indicates operation of a lock and/or that alock has been manually overridden. As still another example, hub 14 mayreceive alert data 308 that indicates that a fall has occurred.

Hub 14 may interpret the received alert data 308 and generate an outputat user interface 314 (e.g., an audible, visual, or tactile output) orremote interface 316 to notify worker 10 or a remote party of the alertcondition (e.g., an operation or override of a lock, that theenvironment is dangerous, that fall protection device 11A ismalfunctioning, that one or more components of fall protection equipment11 need to be repaired or replaced, or the like). In some instances, hub14 may also interpret alert data 308 and issue one or more commands tofall protection device 11A to modify operation or enforce rules of fallprotection device 11A in order to bring operation of fall protectiondevice 11A into compliance with desired/less risky behavior.

In general, while certain techniques or functions are described hereinas being performed by certain components, e.g., PPEMS 6, fall protectiondevices 11, or hubs 14, it should be understood that the techniques ofthis disclosure are not limited in this way. That is, certain techniquesdescribed herein may be performed by one or more of the components ofthe described systems. For example, in some instances, fall protectiondevices 11 may have a relatively limited sensor set and/or processingpower. In such instances, one of hubs 14 and/or PPEMS 6 may beresponsible for most or all of the processing of usage data, determiningconnection status, and the like. In other examples, fall protectiondevices 11 may have additional sensors, additional processing power,and/or additional memory, allowing for fall protection devices 11 toperform additional techniques. Determinations regarding which componentsare responsible for performing techniques may be based, for example, onprocessing costs, financial costs, power consumption, or the like. Theexample techniques may be performed by one or more processors, which maybe processors within fall protection devices 11, hubs 14, PPEMS 6,computing devices 16 and/or 18, and/or safety station 15.

FIG. 14 illustrates a state machine indicating a safety status of a fallprotection device. For ease, the example of FIG. 14 is described withthe example snap hook 220 illustrated in FIG. 10 , but the example isapplicable to the other examples of fall protection devices 11. Also,the example state machine is described starting with safe condition 310.In safe condition 310, the gate movement sensors may be configured togenerate data that indicates that gate 222 is in a closed position.Also, in safe condition 310, computing device 234 may have determinedthat a support structure is within area of attachment 226. For example,computing device 234 may have determined that the summed changes in theresonant frequencies of inductive sensors 230 increased by more than athreshold amount or the rate at which the summed changes in the resonantfrequencies is greater than a threshold rate (e.g., as described aboveusing the operations of FIGS. 4A and 4B and/or FIG. 15 ). Becausecomputing device 234 determined that a support structure is disposedwithin area of attachment 226 and gate 222 is closed, then snap hook 220should be anchored to a support structure, and therefore, in safecondition 310 (e.g., worker 10A is safely tied-off to a supportstructure). In response, computing device 234 may generate informationindicating safe operation, and potentially output such information tohubs 14, safety stations 15, computing device 16, and/or PPEMS 6.

Examples of the information include an electronic message, an audibleoutput, a visual output, and/or tactile output. In some examples, hubs14 may be configured to generate and output information indicating theoperation of snap hook 220. In FIG. 14 , for the various operations,computing device 234 is described as generating information indicatingoperation of snap hook 220. However, hubs 14, safety stations 15,computing devices 16 or 18, and/or PPEMS 6 may generate and output suchinformation.

Subsequent to generating information indicating safe operation,computing device 234 may determine that the support structure is notdisposed within area of attachment 226, but without the gate 222opening. For example, computing device 234 may perform the operationsdescribed in FIGS. 4A and 4B and/or FIG. 15 and determine that thesupport structure is no longer disposed within area of attached 226.However, computing device 234 may have also determined that gate 222never opened. In this case, because it is very unlikely that the supportstructure is no longer present within area of attachment 226 withoutgate 222 opening, computing device 234 may repeat generating informationindicating safe operation. As illustrated in FIG. 14 , once in safecondition 310, regardless of whether computing device 234 determinesthat the support structure is still present or determines that thesupport structure is not present, computing device 234 determines thatsnap hook 220 is in a safe condition as long as gate 222 remained closed(“Gate Closed” of 310).

Subsequent to generating information indicating safe operation,computing device 234 may determine that gate 222 is opened and that thesupport structure is disposed within area of attachment 226 (“Gate Open&& Anchor” of 310). For example, computing device 234 performs theoperations of FIGS. 4A and 4B and/or FIG. 15 and determines that thesupport structure is still within area of attachment 226, but alsodetermines that gate 222 is open. In this example, computing device 234may determine that snap hook 220 is in a sub-optimal condition 320, andgenerate information indicating the sub-optimal operation of snap hook220.

In sub-optimal condition 320, gate 222 is open, but the supportstructure is still within area of attachment 226. Computing device 234may determine that snap hook 220 is in sub-optimal condition 320 as longas gate 222 is open and as long as the support structure is within areaof attachment 226 (“Gate Open and Anchor” of 320). Accordingly,computing device 234 may repeat generating information indicatingsub-optimal operation (e.g., snap hook 220 is in sub-optimal condition320) as long as gate 222 is open and a support structure is within areaof attachment 226 (“Anchor and Gate Open” of 320). If computing device234 determines that gate 222 is closed and determines that the supportstructure is within area of attachment 226 (“Gate Closed and Anchor” of320, then computing device 234 may determine that snap hook 220 is insafe condition 320, and generate information indicating safe operationof snap hook 220.

If, however, computing device 234 determines that gate 222 is open andthere is no support structure within area of attachment 226 (“No Anchor”of 320), then computing device 234 may determine that snap hook 220 isin an unsafe condition 330. Computing device 234 may generateinformation indicating the unsafe operation of snap hook 220. In unsafecondition 330, gate 222 is open and there is no support structure withinthe area of attachment 226.

Once in unsafe condition 330, computing device 234 may determine thatsnap hook 220 is in unsafe condition 330 as long as computing device 234determines that there is no support structure within area of attachment226 (“No Anchor” of 330) or gate 222 is closed (“Gate Closed” of 330).Computing device 234 may therefore repeatedly generate informationindicating unsafe operation until computing device 234 determinessub-optimal operation or safe operation.

For instance, if computing device 234 determines that there is a supportstructure within area of attachment 226, and determines that gate 222 isopen (“Anchor && Gate Open” of 330), then computing device 234 maydetermine that snap hook 220 is in the sub-optimal condition 320.Computing device 234 may then generate information indicating thesub-optimal operation of snap hook 220. Also, as illustrated in FIG. 14, if computing device 234 determines that snap hook 220 is in safecondition 310, but subsequently determines that gate 222 is open andthat there is no support structure within area of attachment 226 (“GateOpen && No Anchor” of 310), computing device 234 may determine that snaphook 220 is operating in the unsafe condition 330. Computing device 234may then generate information indicating the unsafe operation of snaphook 220.

Although the above example techniques are described with respect tocomputing device 234, the example techniques may be performed togetheror in combination with various other processors such as those of hubs14, safety stations 15, computing device 16, and/or PPEMS 6.Accordingly, the example techniques described above for FIG. 14 may beperformed by one or more processors, examples of which includeprocessors within fall protection devices 11, hubs 14, safety stations15, computing device 16, and/or PPEMS 6.

It is to be recognized that depending on the example, certain acts orevents of any of the techniques described herein can be performed in adifferent sequence, may be added, merged, or left out altogether (e.g.,not all described acts or events are necessary for the practice of thetechniques). Moreover, in certain examples, acts or events may beperformed concurrently, e.g., through multi-threaded processing,interrupt processing, or multiple processors, rather than sequentially.

In one or more examples, the functions described may be implemented inhardware, software, firmware, or any combination thereof. If implementedin software, the functions may be stored on or transmitted over acomputer-readable medium as one or more instructions or code, andexecuted by a hardware-based processing unit. Computer-readable mediamay include computer-readable storage media, which corresponds to atangible medium such as data storage media, or communication mediaincluding any medium that facilitates transfer of a computer programfrom one place to another, e.g., according to a communication protocol.In this manner, computer-readable media generally may correspond to (1)tangible computer-readable storage media which is non-transitory or (2)a communication medium such as a signal or carrier wave. Data storagemedia may be any available media that can be accessed by one or morecomputers or one or more processors to retrieve instructions, codeand/or data structures for implementation of the techniques described inthis disclosure. A computer program product may include acomputer-readable medium.

By way of example, and not limitation, such computer-readable storagemedia can comprise RAM, ROM, EEPROM, CD-ROM or other optical diskstorage, magnetic disk storage, or other magnetic storage devices, flashmemory, or any other medium that can be used to store desired programcode in the form of instructions or data structures and that can beaccessed by a computer. Also, any connection is properly termed acomputer-readable medium. For example, if instructions are transmittedfrom a website, server, or other remote source using a coaxial cable,fiber optic cable, twisted pair, digital subscriber line (DSL), orwireless technologies such as infrared, radio, and microwave, then thecoaxial cable, fiber optic cable, twisted pair, DSL, or wirelesstechnologies such as infrared, radio, and microwave are included in thedefinition of medium.

It should be understood, however, that computer-readable storage mediaand data storage media do not include connections, carrier waves,signals, or other transitory media, but are instead directed tonon-transitory, tangible storage media. Disk and disc, as used herein,includes compact disc (CD), laser disc, optical disc, digital versatiledisc (DVD), floppy disk and Blu-ray disc, where disks usually reproducedata magnetically, while discs reproduce data optically with lasers.Combinations of the above should also be included within the scope ofcomputer-readable media.

Instructions may be executed by one or more processors, such as one ormore digital signal processors (DSPs), general purpose microprocessors,application specific integrated circuits (ASICs), field programmablegate arrays (FPGAs), or other equivalent integrated or discrete logiccircuitry, as well as any combination of such components. Accordingly,the term “processor,” as used herein may refer to any of the foregoingstructures or any other structure suitable for implementation of thetechniques described herein. In addition, in some aspects, thefunctionality described herein may be provided within dedicated hardwareand/or software modules. Also, the techniques could be fully implementedin one or more circuits or logic elements.

The techniques of this disclosure may be implemented in a wide varietyof devices or apparatuses, including a wireless communication device orwireless handset, a microprocessor, an integrated circuit (IC) or a setof ICs (e.g., a chip set). Various components, modules, or units aredescribed in this disclosure to emphasize functional aspects of devicesconfigured to perform the disclosed techniques, but do not necessarilyrequire realization by different hardware units. Rather, as describedabove, various units may be combined in a hardware unit or provided by acollection of interoperative hardware units, including one or moreprocessors as described above, in conjunction with suitable softwareand/or firmware.

Various examples have been described. These and other examples arewithin the scope of the following claims.

What is claimed is:
 1. A fall protection device comprising: a body thatat least partially defines an area of attachment for attaching the fallprotection device to a metal support structure; a moveable gateconnected to the body and configured to move between an open positionand a closed position, wherein the open position provides access to thearea of attachment of the fall protection device and the closed positionrestricts access to the area of attachment; an inductive sensor withinthe body for sensing whether the support structure is within the area ofattachment, wherein the inductive sensor is formed on a flexible printedcircuit board that is flexed around a bowl of the body so that aresonant frequency of the electrical circuit of the inductive sensorchanges when the support structure is within the area of attachmentrelative to when the support structure is not within the area ofattachment; and one or more processors configured to determine aresonant frequency change in the electronic circuit of the inductivesensor responsive to the support structure being within the area ofattachment, and determine that the support structure is within the areaof attachment based on the resonant frequency change.
 2. The fallprotection device of claim 1, wherein the electrical circuit of theinductive sensor is positioned and oriented within the body to generate,responsive to current flowing through the electrical circuit, anelectromagnetic field within the area of attachment so that the resonantfrequency of the electrical circuit of the inductive sensor changes whenthe support structure is within the area of attachment and interactswith the electromagnetic field.
 3. The fall protection device of claim1, wherein the electrical circuit of the inductive sensor comprises aninductor having a first conductor formed as a first set of one or morecoils and a second conductor formed as a second set of one or morecoils, and wherein the first conductor and the second conductor areconnected in series to form the inductor, and the first set of one ormore coils are wound in opposite direction relative to the second set ofone or more coils.
 4. The fall protection device of claim 3, wherein theinductor of the inductive sensor has a form substantially similar to alemniscate form.
 5. The fall protection device of claim 3, wherein thefirst set of one or more coils are wound in opposite direction relativeto the second set of one or more coils such that a first signal producedin the first set of one or more coils by an external magnetic field iscancelled by a second signal produced in the second set of one or morecoils from the external magnetic field.
 6. The fall protection device ofclaim 3, wherein the first set of one or more coils and the second setof one or more coils are formed on the same side of a printed circuitboard.
 7. The fall protection device of claim 3, wherein the first setof one or more coils and the second set of one or more coils are formedon opposite sides of a printed circuit board.
 8. The fall protectiondevice of claim 1, wherein the inductive sensor comprises a firstinductive sensor, the device further comprising: at least a secondinductive sensor, wherein a resonant frequency of an electronic circuitof the second inductive sensor changes when the support structure iswithin the area of attachment relative to when support structure is notwithin the area of attachment.
 9. The fall protection device of claim 8,wherein the inductor comprises a first inductor, and wherein the secondinductive sensor comprises a second inductor having a third conductorformed as a third set of one or more coils and a fourth conductor formedas a fourth set of one or more coils, wherein the third conductor andthe fourth conductor are connected in series to form the secondinductor, and the third set of one or more coils are wound in oppositedirection relative to the fourth set of one or more coils.
 10. The fallprotection device of claim 8, wherein the first inductive sensor and thesecond inductive sensor partially overlap.
 11. The fall protectiondevice of claim 1, further comprising a ferrite shielding materialpositioned between the inductive sensor and inner metal of the body. 12.The fall protection device of claim 1, wherein the resonant frequency ofthe electronic circuit of the inductive sensor when the supportstructure is within the area of attachment is at least 5 kilo-Hertz(kHz) greater than the resonant frequency of the electronic circuit ofthe inductive sensor when the support structure is not within the areaof attachment.
 13. The fall protection device of claim 1, wherein theresonant frequency of the electronic circuit of the inductive sensorwhen the support structure is not within the area of attachment isgreater than or equal to 1.0 mega-Hertz (MHz).
 14. The fall protectiondevice of claim 1, wherein the metal support structure is a D-ring. 15.The fall protection device of claim 1, wherein the electronic circuit ofthe inductive sensor further comprises one or more capacitors coupledbetween the first conductor and the second conductor, and in parallelwith the inductor, wherein the inductor and the one or more capacitorsform an LC parallel resonant circuit, wherein when the support structureis within the area of attachment, the support structure causes a changein inductance of the inductor and changes the resonant frequency of theLC parallel resonant circuit.
 16. The fall protection device of claim15, wherein a total capacitance of the one or more capacitors isapproximately 390 pico-Farads (pF).
 17. The fall protection device ofclaim 1, wherein the electronic circuit of the inductive sensor includesan inductor having a width of approximately 9 milli-meter (mm), and alength of approximately 50 mm.
 18. The fall protection device of claim1, further comprising one or more processors configured to: determinewhether the resonant frequency of the electronic circuit of theinductive sensor changed upwards or downwards relative to a baselineresonant frequency of the inductive senor; and determine a type of metalof the support structure based on the determination.
 19. The fallprotection device of claim 1, further comprising: a sensor configured todetermine a position of the moveable gate or a moveable lock thatcontrols the position of the moveable gate.
 20. A system for fallprotection detection, the system comprising: the fall protection deviceof claim 1; a safety harness; and wherein the one or more processors areconfigured to generate information indicating whether the fallprotection device is anchored to the support structure at least based inpart on the determination of whether the support structure is within thearea of attachment of the fall protection device.
 21. The system ofclaim 20, wherein the metal support structure is a D-ring, and whereinthe one or more processors are configured to generate informationindicating safe operation of the fall protection device based on adetermination that the support structure is within the area ofattachment and the gate of the fall protection device is closed.
 22. Thesystem of claim 21, wherein the one or more processors are configuredto: subsequent to generating information indicating safe operation,determine that the gate is opened and that the support structure is notwithin the area of attachment; and generate information indicatingunsafe operation of the fall protection device.
 23. The system of claim22, wherein the one or more processors are configured to repeatgenerating information indicating unsafe operation until determined thatthe gate is closed and that the metal support structure is within thearea of attachment.
 24. The system of claim 20, wherein the fallprotection device is a first fall protection device, wherein the systemcomprises a second fall protection device and wherein the one or moreprocessors are configured to: determine that the first fall protectiondevice is in an unsafe operation and the second fall protection deviceis in a safe operation; determine that a gate of the second fallprotection device is opened; and determine, based at least in part onthe determination that the gate of the second fall protection device isopened, that the second fall protection device is in a sub-optimaloperation.
 25. A method for fall protection detection, the methodcomprising: determining a change in a resonant frequency of anelectronic circuit of an inductive sensor of the fall protection deviceof claim 1; determining whether a support structure is within an area ofattachment of the fall protection device based on the change in theresonant frequency of the electronic circuit of the inductive sensor;and generating information indicating whether the fall protection deviceis anchored to the support structure at least based in part on thedetermination of whether the support structure is within the area ofattachment of the fall protection device.